Gianmarco Alberti

This book offers a clear and accessible guide to cross-tabulation analysis, transforming a complex subject into an accessible topic. It diverges from traditional statistical texts, adopting a conversational tone that addresses common questions and concerns. The author demystifies intricate concepts, with clear explanations and relatable analogies that make the material approachable for readers with varying levels of mathematical expertise.

Unique in its approach, the book avoids overwhelming readers with complex formulas and instead focuses on the principles underlying cross-tabulation analysis. This method ensures that the content is applicable regardless of specific statistical software used, making it a versatile resource.

Targeted at a diverse audience, the book covers the spectrum from foundational elements to comparatively more advanced topics in cross-tabulation analysis. It includes a comprehensive glossary and an appendix of detailed examples, providing practical insight and aiding understanding of key concepts. This book is an invaluable resource for students, researchers, and educators alike, offering a fresh perspective on cross-tabulation analysis that emphasises clarity and practical application.

Key Features:
Employs a conversational style, making complex statistical concepts in cross-tabulation analysis accessible and engaging for all readers.
   
Combines minimal use of formulas with practical examples, ensuring easy comprehension and application, even for those with minimal mathematical background.
   
Features a consistent running example for continuity, complemented by diverse real-world scenarios to solidify understanding of key concepts.
   
Independently valuable without reliance on specific statistical software, emphasising fundamental principles for adaptability across various platforms.
   
Progressively guides readers from foundational basics to comparatively more advanced methods, supplemented by a comprehensive glossary and detailed appendix for an enriched learning.

ISBN 9781032720388
192 Pages 8 B/W Illustrations
July 15, 2024 by Chapman & Hall

Social Organization and Community Practices. Analysis for a reconstruction of the social framework of the Aeolian communities during the Middle Bronze Age PhD dissertation-2012 University of Udine Department of History and Preservation of the Cultural Heritage NOTE: The PDFs of Vol II (Plates) and Catalogue are provided via email upon request. ABSTRACT This study deals with the archaeological evidence from the Middle Bronze Age (ca 1460-1250 BC) settlements on the Acropolis of Lipari, on the Montagnola di Capo Graziano (Filicudi), at Punta Milazzese (Panarea), and Portella (Salina). The work is aimed at the reconstruction of forms of social organization, and is based on the data provided by previous researches carried on those sites. Thanks to those researches, a large amount of data has been made available to scholars interested in a number of different archaeological issues connected to the documentation of the Archipelago. In different points in time studies have been published dealing with the Aegean and Apennine ceramic imports, or with facets of local architecture, or with the problem of the connections between the Aeolian Islands and different parts of Mediterranean shores. The reasons that pushed me to approach the subject of this study can be outlined as follows. While, on the one hand, previous literature has provided important insights into important archaeological issues, on the other hand, a study aimed to investigate the social organization of MBA Aeolian communities was still lacking. It seemed important to this author to understand: a) how the Aeolian MBA communities were organized in the past; b) how material culture was used during daily activities; c) how these are recognizable in the archaeological record; d) where they were performed; e) what relationship existed between those activities and the places where they were performed; f) by what means and for what purposes those activities took place; g) to what extent material culture was used in social relations; h) in more general terms, how and why the material culture could have been expression of the ways in which communities organized themselves, their own life, and their social relations. In this perspective, special interest lies in the possibility to understand how the acquisition and use of exotic goods relates to local practices and indigenous social dynamics. To address these questions, I used a bottom-up approach, which rests on a broad body of evidences of various kind, in a perspective in which the archaeological evidence is analyzed in detail, with attention paid to both the findings and their spatial correlates, to both local and foreign artifacts. The starting point of the research is a small-scale bottom-up analysis, aimed to understand the on-site distribution and associations of objects, and to pinpoint activity areas at the on-site level. In a broader perspective, the analysis is aimed to understand how factors like objects distribution, proportion, occurrence in specific structures, association with other kind of materials, and their occurrence in special areas, can provide insight on the kind and aim of activities performed by past communities. Ultimately, moving to a higher level of interpretation, this may help us understand how life, and the human and social relations, were organized in ancient times. Chapter 1 presents the state of the archaeological researches in the Middle Bronze Age Aeolian horizons. It provides an history of the researches and a description of the various aspects of material culture. Chapter 2 aims to set the archaeological evidence in the broader context of the Sicilian MBA. Chapter 3 reviews the previous literature dealing with the archaeological evidence of the Aeolian Middle Bronze Age. Chapter 4 provides the theoretical framework of this study. It outlines a series of "archeologically significant" questions that are relevant for this study’s sake and that the subsequent sections of the analysis seeks to address. Chapter 5 examines the stratigraphies of the contexts being studied, with the aim to isolate, among the bulk of the published findings, only those that can be linked to the huts’ (final) use. Another topic addressed in this chapter is the quantification of artifacts and their functional classification, the latter to be used for the detection and recognition of activities carried out within the villages. Chapters 6-9 present an in-deep analysis of findings and stratigraphies from each village structure (huts and open areas). Chapter 10 analyzes the distribution of findings and functional classes of objects within and between the structures of each settlement. On the basis of analytical results derived from previous Chapters 6-9, the analysis is able to take into consideration cluster of objects from layers which may be considered relative to the last phase of use of each structure. The on-site distribution of findings and functional classes of objects is put in relation to other kind of data and evidences, such as the size of the structures, dimensional features of the objects, the distribution of certain decorative schemes on specific ceramic forms. For Lipari, the analysis seeks to integrate the faunal evidence with data relative to other classes of materials (ceramic, lithic). For each settlement, a final paragraph provides a sinthesis of the main achivements stemming from the analysis. Chapter 11 discusses the achievements of the preceding sections, and try to read them in the light of the theorethical background provided in Chapter 4. On these basis, a reconstruction and interpretation of forms of community organization is proposed. Chapter 12 provides a summary of the main achievements of the work. Building on the analysis object of Chapters 10-11, a number of aspects relevant to the social organisation of the Aeolian MBA communities are higlighted. To quote just a few: -localisation of specific activity areas; distinction bewteen domestic and utilitarian huts; -identification of the spatial and material correlates of both types of structures; -identification of practices for the promotion of social solidarity by means of feasting activities and the use of a shared decorative symbolism; -individuation of forms and loci of social integration between autonomous nuclear families with the aim to mitigate the forms of social tension; -reconstruction of a social framework allowing to give a sounder explanation of why and in which way exotica [both of Aegean and Apennine type] were integrated and recontextualizated by local communities in local social-oriented practices. Finally, Appendix 1 aims to clarify the basis of the dimensional classification of the Milazzese huts used in the analytical sections of the work. Appendix 2 provides a primer on the Correspondence Analysis, an explorative statistical technique used in Chapter 10 to identify similarities and differences between the structures of the various settlements, on the basis of the proportion of artifacts that make up the huts’ inventories.

This study deals with the ceramic repertoire of the Aeolian Middle Bronze Age culture, the so called Milazzese facies. The work takes into account the edited documentation from the four main settlements on the Aeolian Archipelago, unearthed by Luigi Bernabò Brea in several excavations between 1940 and 1970. These settlements are on the Montagnola of Filicudi, the Acropolis of Lipari, Capo Milazzese at Panarea, and at Portella on the island of Salina. At the latter site, more recent excavations are also taken into account in this present study. The aim of this work is twofold: to devise a formalized typology for the Milazzese ceramic repertoire (to be used as a basis for the chrono-typological analysis of the pottery assemblages) and to assess the chronological and typological achievements in an historical and, broadly speaking, cultural perspective. Chapter 1 provides a description of the Milazzese facies and of the various aspects of its material culture. Chapter 2 deals with the problem of the stratigraphy of the Aeolian MBA settlements. Chapter 3 looks at Aegean pottery from Milazzese contexts. Chapter 4 devises a formalized typology for the Milazzese pottery assemblage. Chapter 5 deals with the seriation of the Milazzese ceramic assemblage. Chapter 6 describes the Milazzese ceramic repertoire’s development and attempts to read this phenomenon in a cultural perspective. Three data Appendices and catalogue are provided.

One of the most debated and explored period of the prehistory of Sicily is the Middle Bronze Age (15th-13th century BCE), which is considered as a crucial moment for the development of local prehistoric social, economic, and cross-cultural dynamics. The local Thapsos culture is what best represents this chronological period and is characterized at some sites by the occurrence of datable ceramic imports from the Aegean alongside their local replicas. These have helped researchers with establishing a local relative chronology based indirect beacons with eastern Mediterranean contexts. However, when it comes to an independent absolute chronology for MBA context in mainland Sicily, no recent program of radiocarbon dating has been carried out so far. In this contribution, the authors devise a Bayesian model based on evidence from a stratified MBA context at St. Ippolito (Caltagirone, central-eastern Sicily) where a set of seven samples have been radiocarbon dated. The study aims to assess which part of the overall development of the MBA the analyzed context corresponds to, to absolute date the activities represented by the deposit's layers, and to lay the basis to tentatively bracket in time the use of some associated ceramic materials.

Cost-surface and least-cost path analyses are widely used tools to understand the ways in which movement relates and engages with the surrounding space. They are employed in research fields as diverse as the analysis of travel corridors, land accessibility, site locations, maritime pathways, animal seascape connectivity, transportation, search and rescue operations. This work describes the ‘movecost’ package, designed for the free R statistical environment, which provides the facility to produce, in a relatively straightforward way, various accumulated slope-dependent cost surfaces and least-cost outputs from different models of movement across the terrain. The package motivation and significance are described, and the main software characteristics are outlined by means of an illustrative example.

Cost-surface analysis in Geographic Information System (GIS) environment has been less frequently used in the study of ancient sail navigation than in other studies of the human past. Navigation cost-surface analysis entails the use of GIS tools that are versatile but not very easy to grasp and to put to work. This article describes an ArcGIS toolbox built to facilitate cost-surface analysis of ancient sail navigation. It estimates the navigation time from a start location, considering parameters relevant for the generation of an accumulated anisotropic cost-surface, automating the complex workflow required to meaningfully pre- and post-process the data. Acknowledging the limitations inherent to the tool, and to the modeling of a complex matter such as sail navigation, the toolbox is first described and then used in a worked example. Historically recorded voyages in the Mediterranean during classical antiquity are compared to estimated durations generated by the toolbox. In spite of structural and expected limitations, the results indicate that the proposed toolbox may produce reasonable estimates. These should be thought of as values gravitating around, not matching, likely past durations. The estimated values may prove useful as an indication of the order of magnitude of past voyages’ duration, and as frame of reference in measuring ancient maritime space through time.

Settlement and social organization in Middle Bronze Age Sicily (ca 1490–1250 BCE) have received scant attention compared to that devoted to broader cultural processes during the same period. In spite of some limitations, this work aims at filling the gap building on published evidence from Capo Milazzese settlement (Aeolian Archipelago, north-eastern Sicily), which is taken as case study. On the basis of a preliminary yet necessary study of deposits' formation process, and by means of quantitative and multivariate analyses, this work seeks to pinpoint the activities performed within the settlement, and to understand their material and spatial correlates. For the first time, this work identifies habitations and utilitarian huts highlighting differences in terms of artefacts inventories and floor area. Evidence hinting at huts' functional changes, and at special activities such as pottery production, is located. The material culture patterning brought to the fore by the analysis provides grounds to infer traits of households' socio-economic, architectural, and spatial organization, and to open a window into local processes that may account for the social meaning of food consumption practices, and for the incorporation of foreign pottery into local ceramic inventories.

Johnson’s scalar stress theory, describing the mechanics of (and the remedies to) the increase in in-group conflictuality that parallels the increase in groups’ size, provides scholars with a useful theoretical framework for the understanding of different aspects of the material culture of past communities (i.e., social organization, communal food consumption, ceramic style, architecture and settlement layout). Due to its relevance in archaeology and anthropology, the article aims at proposing a predictive model of critical level of scalar stress on the basis of community size. Drawing upon Johnson’s theory and on Dunbar’s findings on the cognitive constrains to human group size, a model is built by means of Logistic Regression on the basis of the data on colony fissioning among the Hutterites of North America. On the grounds of the theoretical framework sketched in the first part of the article, the absence or presence of colony fissioning is considered expression of not critical vs. critical level of scalar stress for the sake of the model building. The model, which is also tested against a sample of archaeological and ethnographic cases: a) confirms the existence of a significant relationship between critical scalar stress and group size, setting the issue on firmer statistical grounds; b) allows calculating the intercept and slope of the logistic regression model, which can be used in any time to estimate the probability that a community experienced a critical level of scalar stress; c) allows locating a critical scalar stress threshold at community size 127 (95% CI: 122–132), while the maximum probability of critical scale stress is predicted at size 158 (95% CI: 147–170). The model ultimately provides grounds to assess, for the sake of any further archaeological/anthropological interpretation, the probability that a group reached a hot spot of size development critical for its internal cohesion.

This article focuses on the Early–Middle Bronze Age (MBA) transition in Sicily and southern Italy from a Bayesian radiocarbon perspective. The aims are to: (i) estimate the beginning of the MBA (i.e. Thapsos– Milazzese culture in Sicily; Apennine culture in southern Italy) at four key-sites; (ii) assess the existence of a site- wide variability; and (iii) understand if an offset is likely to have existed between the beginning of the MBA and the Aegean Late Helladic (LH) IIIA phase, which currently marks the start of the MBA. The study indicates that the MBA probably started earlier at Portella (95.4% range 1541–1430, mode 1465 BC) and Roca Vecchia (1706–1394, mode 1460 BC) than at Coppa Nevigata (1527–1292, mode 1410 BC; or 1490–1265, mode 1380 BC) and Ustica (1609–1261, mode 1405 BC). Also, the beginning of the MBA at Portella and Roca Vecchia is probably earlier than that of the LH IIIA. This suggests that the current synchronization between MBA and LH IIIA, based on historical grounds, needs revision as radiocarbon evidence points to an earlier start of the MBA at two of the four sites. Overall, by means of scientific dating methods and Bayesian modelling, the study allows us to set in a different perspective the chronology proposed in the current literature based on historical synchronizations

The use of contingency tables is widespread in archaeology. Cross-tabulations are used in many different studies as a useful tool to synthetically report data, and are also useful when analyst wishes to seek for latent data structures. The latter case is when Correspondence Analysis (CA) comes into play. By graphically displaying the dependence between rows and columns, CA enables the analyst to explore the data in search of a meaningful inner structure. The article aims to show the utility of CA in archaeology in general and, in particular, for the identification of areas devoted to different activities within settlements. The application of CA to the data from a prehistoric village in north-eastern Sicily (P. Milazzese at Panarea, Aeolian Islands-Italy), taken as a case study, allows to show how CA succeeds in pinpointing different activity areas and in providing grounds to open new avenues of inquiry into other aspects of the archaeological documentation.

This paper proposes a Bayesian model for the 14C chronology of Sicilian Early and Middle Bronze Age, with a specific focus on the northeastern sector of the island. Building on the available 14C determinations, the model allows addressing a number of chronological questions left open in literature, making a first step toward an independent absolute chronology. The analysis put the start of the earlier part of Early Bronze Age (Capo Graziano 1-Casa Lopez phase) between 2400-2175 cal BC, and the end at about 1960 cal BC. The advanced stage of the same period (Capo Graziano 1-Filo Braccio phase) is likely to have started and ended around 1960 and 1730 cal BC respectively. The model indicates that the time slot with the highest posterior probability for the start of the Middle Bronze Age-Milazzese (Portella phase) is between 1490 and 1460. This turns up to be earlier than held to date. Notably, the model enables for the first time to bracket the development of the later stage of Early Bronze (Capo Graziano 2-M. di Capo Graziano phase) between 1730 (end of Filo Braccio phase) and 1490/60 cal BC (start of Middle Bronze Age-Portella phase). The latter date is earlier than usually held for the end of Capo Graziano 2. The existence of a narrow gap between the end of the latter and the start of Portella phase is tentatively proposed only on stratigraphic grounds. Further, the analysis enables for the first time to pinpoint and quantify the lag that is likely to have existed between the start of those Sicilian prehistoric phases and the appearance of Late Helladic imports. The comparison with the Aegean 14C Bayesian chronology indicates that a time lag (about 45 yr) is likely to have occurred between the start of Capo Graziano 2 and of the Late Helladic period. A time lag between 20 and 70 yr is likely to have existed between the start of the Sicilian Middle Bronze Age and of the Late Helladic III. Arguments tentatively supporting the narrower interval are also discussed.

This paper deals with radiocarbon determinations from the Middle Bronze Age site of Portella on the island of Salina (Aeolian Archipelago, Italy). The available 14C evidence is taken into account, in a simple Bayesian model, in order to explore the issue of the absolute chronology of both the settlement and the stage of the local cultural sequence to which Portella belongs. A high date is proposed for the start of the Aeolian (and Sicilian) Middle Bronze Age: 1556–1422 cal BC (95.4% confidence), with a a most likely (modal) date of about 1450 cal BC. Further, the analysis suggests that the Portella phase is likely to have been a very short one, with a span of 0–65 yr (68.2%) or 0–131 yr (95.4%). The archaeological implications are explored. The relation of these results to the evidence of ceramic phasing is also considered. Since Aegean datable ceramic imports are documented in Aeolian/Sicilian Middle Bronze Age contexts, the connection between Portella’s chronology and the absolute dating of one of the Aegean phases (namely, Late Helladic IIIA1) is also investigated.

This paper is faced with the problem of the relative and absolute chronology of the first two phases of Thapsos’ residential quarter. It is well known that the phasing put forward by the excavator (G. Voza) is in contrast with the traditional Sicilian cultural sequence outlined by L. Bernabò Brea. In Bernabò Brea’s view, the Thapsos period (Middle Bronze Age), spanning from XIV BC down to the first quarter of XIII BC, was followed by the Pantalica North period (Late Bronze Age) from about middle XIII BC onward. Voza, on the basis of his excavations at the Thapsos’peninsula between the 70’s and 80’s of the past century, isolated three different phases: the first two belonging to the Thapsos period, the third to the Final Bronze Age. The first, characterized by round huts with annexes, was dated to the XIV BC, while the second, with its rectangular complexes, was ascribed to the XIII-XII BC. In this view, Thapsos’ second phase was contemporary to the Pantalica North culture. It becomes clear that the topic of the chronology of Thapsos’ residential quarter is of utmost relevance in the frame of the cultural sequence in eastern Sicily. This paper is aimed to ascertain if and how the chronology of the ceramic items from Thapsos’ residential quarter could shed a new light on the problem of Voza’s phasing. The author attempts to take into account distribution, provenance and possible chrono- logy of both imported (Maltese-Borg in-Nadur) and local wares (the latter bearing Mycenaean-inspired decorative motives), in order to critically review the absolute and relative dating of the structures. He proposes a chronology that is alternative, but no always incompatible, to that previously put forward. The author proposes: a) to lower down to the early XIII BC (parallel to the early MIC IIIB) the chronology of the later use of Thapsos’ northern quarter with round huts (Voza phase I); b) the items from the Complex B are not consistent with a date later that the early XIII BC; the possible provenance of these items from a use-level of the structure leads to believe that this Complex was build during the XIV BC, claiming, therefore, a dating earlier than the traditional one as well as a period of coexistence between round huts and complex structures; c) in lack of any good chronological hint, the Complex A is dated on the grounds of its typological consistence with the Complex B; d) only for the Complex C it can be assumed a period of re-use during the Final Bronze Age. Finally, these remarks are related to other data. On the one hand, it is stressed the synchronism between the construction of the Complexes and the social stratification in act in the Thapsos’ society during the same period; on the other hand, it is stressed the existence at Cannatello (Middle Bronze Age settlement) of a situation similar to that of Thapsos, as far as the coexistence of round and rectangular structures during the XIV BC is concerned.

Tha aim of this work is to sketch a picture of the social stratification of the Thapsos’ centre (the name-site of the sicilian Middle Bronze Age), filling a gap in the litterature avalaible so far. This analisys is based upon the funerary data provided by the rock-cut tomb cemetery of the centre. Within a strongly context-oriented framework, we shall seek to distinguish each funerary assemblage (in each fase of the Thapsos’ cemetery) on the basis of its quali- tative and quantitative composition. We intend: a) to highlight the various levels of “richness” of the tombs and of the related uman groups; b) to compare the value of the different classes of items of the funerary assemblages; c) to seek the correspondece between particular objects and specific uman groups, trying to explain this link with special attention to the class of the imported ceramics and to that of the formal imitation of foreign pottery; d) to verify if this correspondece can shed light over the social role of the uman groups. Moreover, we shall seek to compare the data as they come from tomb contex- ts with the few ones at our disposal from the residential quarter. We shall valuate if the different levels of richness are consistent with the architectural features of the tombs, e.g. dimensions/volume of the chamber and other elements like the tholoi-like profile of the grave. Finally, we shall try to give a hystorical interpretation of the data.

With few ground-breaking exceptions, mainly framed in the context of archaeological research, GIS and quantitative methods have not been used so far in Malta to better understand the development and layered making of the landscape in relatively recent historical times. The present work aims at describing the main achievements of the authors’ research (developed in the context of the five-year ERC-funded FRAGSUS project) into the Maltese economic and historical landscape and will provide insights into how modern GIS-based quantitative approaches can be used in conjunction with qualitative data (for instance, cadastral maps and ethnographic accounts) to shed light on human-environment interaction in Malta during the last two centuries.

Correspondence Analysis has become increasingly popular in archaeology to visualize contingency tables and to understand their structure. As an exploratory tool, the technique has found wide use for a variety of purposes, encompassing (but not limited to) activity areas research, analysis of pottery distribution among a variety of contexts, study of faunal remains, and chronological seriation. This entry provides a short jargon-free description of the technique, and of its rationale and context of use. Some aspects crucial to the interpretation of the results, such as the number of dimensions to consider relevant for the interpretation, the contribution of the categories to the construction of the dimensions, and the quality of the points' display, are synthetically discussed. The use of Correspondence Analysis to formally seek for clusters, and/or to achieve an optimal ordering of rows and columns (e.g., for the purposes of chronological seriation), is also described. Reference is finally made to a number of free software that implement the technique.

Among the Cypriot pottery from local Middle Bronze Age tomb contexts of south-eastern Sicily, Base Ring II jugs remain somewhat unexplored under the prospective of both chronology and possible manufacture centre. As to the latter issue, different opinions exist: Levantine, Cypriot, or local (or even Aegean) origin. In the author’ view, a better definition of the chronology of the jugs can shed light on the problem of the manufacture centre. In this paper, it will be attempted to pinpoint the chronology of the entrance of the jugs in the local contexts on the ground of both typological and contextual data. Then, the technical, stylistic and typological features of the Cypriot and Levantine specimens will be taken into account, in order to evaluate whether or not they are consistent with the features of the “Sicilian” jugs. For these purposes, the relation between the chronology of the Levantine Cypriot-type imitations and the date suggested for the Sicilian specimens will be considered. It follows the hypothesis of the Levantine production is questionable, on stylistic, technical, and chronological grounds. The consistence of some of these features with a genuine Cypriot manufacture is stressed.

"Thapsos is the name-site of the Sicilian Middle Bronze Age. It lies in south-eastern Sicily, in the gulf of Augusta, on
a low lying limestone promontory connected to the mainland by a narrow isthmus. The site was systematically investigated by Paolo Orsi at the end of XIXth century: these first researches were focused on the cemetery of rock-cut tombs, lying in the north-eastern part of the site, that yielded the first bulk of the local grey hand-made pottery along with a number of Mycenaean vessels. In the same period (between the end of XIXth and the first years of XXth century) Orsi unearthed a group of Middle Bronze Age cemeteries, lying round the eponymous centre: Cozzo del Pantano, Plemmirio, Matrensa, Molinello. These centres yielded both the local pottery and few Mycenaean imports. In this area the archaeological researches were resumed between the end of 1960’s and the first half of 1980’s and were for the first time focused on the residential quarter lying on the isthmus of Thapsos’ site. Two elaborate rectangular complexes were unearthed, standing out from the circular huts of local tradition. The two structures were regarded, although not unanimously, to be of Mycenaean inspiration, similar to that found in the tholoi-like profile of few rock- cut tombs. In these years a new area of the Thapsos’ cemetery were investigated: the tombs A1 and D yielded local vessels along with Mycenaean and Cypriot pots.
Despite the knowledge of the Middle Bronze Age culture in south-eastern Sicily grew enormously in the second half of the past century, the aspect of the chrono-typological seriation of the Thapsos’ ceramic repertoire was so far neglected. This paper will firstly try to fill this gap, working on the bulk of pottery so far published: we will take into account the tombs with few burials in order to sketch out a possible development of the local pottery’s types; we will distinguish, therefore, three different phases. On the grounds of the association with Mycenaean pots within the local contexts and/or using the cross-dating with other contexts and/or on the basis of the influence of Mycenaean pottery on the local types, we will link our phases to the MIC IIIA1, MIC IIIA2 and MIC IIIB1. The characteristic types and decorations of each phase will be taken into account in order to find out the so called “fossili guida” of the repertoire; we will point out the ties (and/or the differences) with both the preceding Early Bronze Age cultures (facies of Castelluccio and Rodì-Tindari-Vallelunga) and the contemporary Aeolian Milazzese culture. We will take into consideration, moreover, the influence of the Mycenaean culture on the local repertoire in terms of both pottery types and decorations; this topic will be useful, moreover, in order to find out the lower chronological term of the Thapsos’ sequence, which we fix, like we said above, to the early part of MIC IIIB. Subsequently, on the grounds of the different trends of use of the cemeteries under discussion, this paper will be focused on sketching out the historical dynamics involving south-eastern Sicily in the Middle Bronze Age, with special attention to the problematic cultural and chronological relationship with the following Pantalica Nord culture. During our last phase only Thapsos (and, possibly, Cozzo del Pantano) survives, while the other sites (Plemmirio, Matrensa, Molinello) seem to disappear. In the same moment the presence of few (but meaningfully late in date) Thapsos’ sherds found at Pantalica (the name-site of the Late Bronze Age) could be explained with the transfer of people from the coast. This insecurity’s sign could be linked to the Siculi’s invasion from the Italian peninsula, which leads destructive effects on the Aeolian islands. Moreover, was this “geo-political” situation encouraged by the first problems suffered by the Mycenaean centres? In conclusion, as regards the relation between Thapsos and Pantalica Nord, our analysis agrees with the recent overall study of the Late Bronze Age culture and strengthens the Bernabò Brea’s historical frame based on the diachronic sequence between the Middle Bronze and Late Bronze Age cultures."

"Two (local) Middle Bronze Age sites in Sicily are known for having yielded Cypriot imports: Thapsos to southeast, and Cannatello in the south-central part of the island. These imports come from contexts with a strong intercultural character, as they are featured by the presence of items from other Mediterranean areas, especially Mycenaean Greece. Moreover, the existence of bronze working activities is documented in these sites. Thapsos and Cannatello belonged to a wider network of Middle Bronze Age sites, covering the whole Sicily (from the island of Ustica to the Aeolian Archipelago and, moving southward, Madre Chiesa).
The task of this paper is twofold and deals primarily with the documentation of south-eastern Sicily. The evidence of Cannatello is taken into account in a comparative perspective. The author will firstly attempt to stress some key elements in the problem of the chronology and origin of the Base Ring II juglets from Thapsos’ contexts in south-eastern Sicily. Their origin is, in fact, debated, since two different hypotheses were put forward by scholars: Levantine and local. Taking into account some contextual and chronological data, the author suggests discarding the Levantine hypothesis.
In the second part of the paper, the author will focus on the existence of other goods, yielded mainly by Thapsos tomb contexts, that could be ascribed to Cypriot trade and that could have been arrived to Sicily along with Base Ring II juglets, if the latter are to be considered of Cypriot origin (in this author’s opinion). On the grounds of compositional analysis of grave assemblages, the different use and appreciation of the juglets at Thapsos will be stressed in comparison with other parts of the Mediterranean area. The same is done in relation to other Cyprus-related items, like the Cypriot- fashioned local handmade bowls, objects of the author’s earlier work. It becomes clear that Cyprus- related items at Thapsos are strictly connected to the high-status segment of the local society. To this author’s mind, these ties can give reason to link Thapsos and Cyprus: Thapsos’ elite kept under control the local bronze dagger production and this needed raw material (copper and/or tin) provided by Cypriot counterparts. The role of the local elite in Cypriot long-distance movements will also be explored. It must be stressed that a Thapsos’ type dagger was present aboard the Uluburun ship. This study enables to make some further remarks on the geopolitical condition of the eastern Mediterranean area at the close of the fourtheenth century BC and on its possible drawbacks for Thapsos èlites’ interests."

Introducing "stratastats", your go-to R package for stratified data analysis. It's packed with advanced tools including odds ratios, chi-squared tests, and the Cochran-Mantel-Haenszel (CMH) and Breslow-Day (DB) tests for assessing association and homogeneity. Coupled with clear interpretation guidelines, it may prove valuable for epidemiologists, market researchers, and social scientists. Master stratified data analysis and interpretation with ease! Available from CRAN: https://CRAN.R-project.org/package=stratastats

This vignette aims at showing the use of the current version of the 'chisquare' package. Analyze categorical data effortlessly, derive insights from cross-tabulations, and visualize significant associations with ease. Perfect for researchers and data enthusiasts! It is available from CRAN.

This vignette aims at showing the use of the current version of the landform package. It allows classify a landscape into different categories based on the Topographic Position Index (TPI) and slope. It offers two types of classifications: Slope Position Classification (Weiss 2001) and Landform Classification ( Weiss 2001 ; Jenness 2003). The package will be released on CRAN in mid-August 2023.

This document provides an introduction to the caresid R package. The package contains a function of the same name, caresid() , that allows to carry out Correspondence Analysis (CA) on an input contingency table and to create a scatterplot of the row and column points on the selected dimensions. More importantly, the function can add segments to the plot to visualize significant associations between row and column categories on the basis of positive (unadjusted) standardized residuals (hereafter, residuals) larger than a given threshold. The segments can be optionally labelled with the corresponding residual value. The package will be released on CRAN in mid-June 2023

The document provides an introduction to the 'boxplotcluster' R package. The package contains a function of the same name, boxplotcluster, that implements a special clustering method based on boxplot statistics. Version 0.2 will be released on CRAN in June 2023.

This vignette aims at showing the use of the current version of the caplot package. It allows to perform Correspondence Analysis on the input dataframe and plots the results in a scatterplot that emphasizes the geometric interpretation aspect of the analysis (see Borg-Groenen 2005 ; Yelland 2010 ). It is particularly useful for highlighting the relationships between a selected row (or column) category and the column (or row)
categories.

This vignette aims at showing the use of version 0.2 of the brsim package. To hopefully enhance clarity, it is organised as a sequence of tasks. For more details about the brsim() function, its parameters, for the returned values, and for relevant literature, users are referred to the package’s help documentation. Version 0.2 will be released to CRAN in June 2023.

The 'brsim' package provides the facility to calculate the Brainerd-Robinson similarity coefficient for the rows of an input table, and to calculate the significance of each coefficient based on a permutation approach. Optionally, hierarchical agglomerative clustering can be performed and the silhouette method is used to identify an optimal number of clusters.

Available from CRAN (https://CRAN.R-project.org/package=brsim)

Provides the facility to perform the chi-square and G-square test of independence, calculates permutation-based p value, and provides measures of association such as Phi, odds ratio with 95 percent CI and p value, adjusted contingency coefficient, Cramer's V, bias-corrected Cramer's V, Cohen's w, Goodman-Kruskal's lambda, gamma, and tau, Cohen's k. It also calculates standardized and adjusted standardized residuals, and their significance. Different outputs are returned in nicely formatted tables.
Available on CRAN: https://CRAN.R-project.org/package=chisquare

This vignette aims at showing the use of the current version of the movecost package and of its functions. To hopefully enhance clarity, it is organised as a sequence of tasks. In-built datasets will be used throughout this document. For more details about each function’s parameter, for the values returned by each function, and for relevant literature, see the package’s help documentation.

For an updated version of the vignette, please visit https://drive.google.com/file/d/1gLDrkZFh1b_glzCEqKdkPrer72JJ9Ffa/view

The package contains many functions useful for univariate outlier detection, permutation-based t-test, permutation-based chi-square test, visualization of residuals, and bootstrap Cramer's V, plotting of the results of the Mann-Whitney and Kruskall-Wallis test, calculation of Brainerd-Robinson similarity coefficient and subsequent clustering, validation of logistic regression models, optimism-corrected AUC, robust Bland-Altman plot, calculation of posterior probability for different chronological relationships between two Bayesian radiocarbon phases, point pattern analysis, landform classification, clustering of spatial features. Available on CRAN (https://cran.r-project.org/package=GmAMisc)

The package allows to plot a number of information related to the interpretation of Correspondence Analysis' results. It provides the facility to plot the contribution of rows and columns categories to the principal dimensions, the quality of points display on selected dimensions, the correlation of row and column categories to selected dimensions, etc. It also allows to assess which dimension(s) is important for the data structure interpretation by means of different statistics and tests. The package also offers the facility to plot the permuted distribution of the table total inertia as well as of the inertia accounted for by pairs of selected dimensions. Different facilities are also provided that aim to produce interpretation-oriented scatter-plots. URL: https://cran.r-project.org/package=CAinterprTools

The package provides the facility to calculate accumulated cost surface,  least-cost paths, and least-cost corridors using a number of human-movement-related cost functions that can be selected by the user. It just requires a Digital Terrain model, a start location and (optionally) destination locations.
URL: https://cran.r-project.org/package=movecost

'plotJenks' is an R function which allows to break a dataset down into a user-defined number of breaks and to nicely plot the results, adding a number of other relevant information. Implementing the Jenks' natural breaks method, it allows to find the best arrangement of values into different classes.

'ca.percept' is a R function which allows to plot a variant of the traditional Correspondence Analysis scatterplots that allows facilitating the interpretation of the results. In particular, the function aims at producing what in marketing research is called perceptual map.
This function aims at producing that kind of visual representation of the CA results that seeks to avoid the problem of interpreting inter-spatial distance (M. T. Bendixen, Compositional Perceptual Mapping Using Chi-squared Trees Analysis and Correspondence Analysis, Journal of Marketing Management 11, 1995, 571-581), by plotting only one type of points (say, column points), and "giving names to the axes" corresponding to the major row category contributors to the two selected dimensions.

Please: preferentially refer to http://cainarchaeology.weebly.com/r-function-for-perceptual-map-like-ca-scatterplot.html to check for updated/improved versions of the function.

'log.regr' is an R function which allows to make it easy to perform binary Logistic Regression, and to graphically display the estimated coefficients and odds ratios. It also allows to visually check model's diagnostics such as outliers, leverage, and Cook's distance.

Please: preferentially refer to http://cainarchaeology.weebly.com/r-function-for-binary-logistic-regression.html to check for updated/improved versions of the function.

'perm.t.test' is an R function which allows to perform a permutation-based t-test to compare two independent groups. The test's results are graphically displayed within the returned chart. A permutation t-test proves useful when the assumption of 'regular' t-test are not met. In particular, when the two groups being compared show a very skewed distribution, and when the sample sizes are very unbalanced.
NOTE: please, refer to http://cainarchaeology.weebly.com/r-function-for-permutation-t-test.html to check for new improved versions of the function

'ca.plus' is a R function which allows to plot Correspondence Analysis scatterplots modified to help interpreting the analysis' results. In particular, the function aims at making easier to understand in the same visual context (a) which (say, column) categories are actually contributing to the definition of given pairs of dimensions, and (b) to eyeball which (say, row) categories are more correlated to which dimension.

'model.valid' is an R function which allows perform internal validation of a binary Logistic Regression model, implementing part of the procedure described by:
Arboretti Giancristofaro R, Salmaso L. Model performance analysis and model validation in logistic regression. Statistica 2003(63): 375–396.

'auc.adjust' is an R function which allows to calculate the AUC of a (binary) Logistic Regression model, adjusted for optimism. In essence, the function performs an internal validation of a model via a bootstrap procedure (devised by Harrell et al) , which enable to estimate the degree of optimism of a fitted model and the extent to which the model will be able to generalize outside the training dataset.
The function is quite straightforward:
auc.adjust(data, fit, B)
where:
data is a dataframe containing your dataset (note: the Dependent Variable must be stored in the first column to the left),
fit is the object returned from glm() function,
B is the desired number of bootstrap resamples (suggested values: 100 or 200)
The boxplots represent:
-the distribution AUC value in the bootstrap sample (auc.boot), which represents "an estimation of the apparent performance";
-the distribution of the AUC value deriving from the model fitted to the bootstrap samples and evaluated on the original sample (auc.orig), which represents test performance (i.e., the model performance on independent data).
At the bottom of the chart, the apparent AUC (i.e., the value deriving from the model fitted to the original dataset) and the AUC adjusted for optimism are reported.

'scalar.stress' is an R function which allows to calculate probability that a community reached a critical level of scalar stress, on the basis of its community size. For a in-deep discussion of the theoretical background and of the rationale on which the calculation is based (namely, a Logistic Regression model base on data for Hutterite communities fission), see my 2014 article Modeling Group Size and Scalar Stress by Logistic Regression from an Archaeological Perspective.

The function returns:
a) a chart representing: the scalar stress as function of increasing community size; the critical community size threshold with its 95% confidence interval (blue lines) and the observed community size (i.e., the value of x fed into the function); at the bottom of the chart, the observed community size, the point estimate of the probability of critical scalar stress (and its 95% confidence interval) are reported. This last piece of information is visually represented in the second returned chart, described below;

b) a second chart represents the probability of critical scalar stress as (logistic) function of community size; a vertical red line indicate the observed community size, while three horizontal lines represent the point estimate and its 95% confidence interval [dashed lines] for the probability of critical scalar stress.

A number of interesting packages are available to perform Correspondence Analysis in R. At the best of my knowledge, they lack some tools to help users to eyeball some critical CA aspects (e.g., contribution of rows/cols categories to the principal axes, quality of the display,correlation of rows/cols categories with dimensions, etc). Besides providing those facilities, this package allows the users to calculate the significance of the CA dimensions by means of the 'Average Rule', the Malinvaud test, and by permutation test. Further, it allows to also calculate the permuted significance of the CA total inertia. The package comes with a dataset (greenacre_data) after Greenacre 2007 (p. 90, exhibit 12.1).

The package allows to plot a number of Correspondence Analysis information such as the contribution of rows and columns categories to the principal axes, the quality of points display on selected dimensions, the correlation of row and column categories to selected dimensions, etc. It also allows to assess which dimension(s) is important for the data structure interpretation by means of the so called 'Average Rule'. Moreover, it implements the Malinvaud test, which test the significance of the table dimensions. The package also offers the facility to plot the permuted distribution of the table total inertia as well as of the inertia accounted for by pairs of selected dimensions. The two latter facilities allows to test the significance of the total inertia and of the dimensions the user is interest in. For more details about the rationale behind the use of the implemented CA interpretation facilities, see the journal article Alberti 2013 cited below. As to the situations in which permutation test can be applied to CA (e.g., to assess the significance of the dimensions), see Greenacre 2007 (198-199).

CAseriation allows to sort the rows and columns of the input contingency table according to the scores of rows and columns on the Correspondence Analysis' dimension selected by the user. The package also allows to plot the CA scatterplot of selected dimensions, and to seek for clusters in the dataset. As for seriation, two plots are returned, displaying the sorted contingency table. The results are also exported into an Excel spreadsheet.

In archaeology there is often the need to seriate contingency tables in order to devise a relative chronology of different types of contexts (e.g., graves). Different approaches exists in literature to achieve a best ordering. The method implemented in the 'CAseriation' package is the ordination of rows and columns of a contingency table according to their scores on the Correspondence Analysis' dimension selected by the user.

The ideal workflow for the use of the package would be:

(a) fed the contingency table into R;

(b) inspect the Correspondence Analysis scatterplot in search of a seriation structure (i.e., presence of the 'horseshoe' effect);

(c) sort the table according to the dimension the user is interesting in;

(d) additionally, formally assess the existence of clusters in the data.

Implemented functions to achieve the above goals:

(b) check.ca.plo()

(c) sort.table()

(d) plot.clusters.rows(); plot.clusters.rows()

The package provides the facility to assess to what extent the seriation structure (if any) embedded in the data approximates to a 'perfect' seriation. This can be accomplished by means of the evaluate() function, which returns the Correspondence Analysis scatterplot for row/column categories and add a 2order polynomial fit. The Rsquared value is reported in the plot's subtitle.

'ca.scatter' is an R function which allows to plot different types of Correspondence Analysis scatterplots. It depends on the 'ca' and 'FactoMineR' packages, and aims at making easier to obtain some of the interesting charts provided by those two amazing packages. Users are refereed to the aforementioned packages in case they want greater control of some settings.

The function is quite straightforward:
ca.scatter(data, x, y, type)

where data is the input dataset, x and y are the dimensions of interest, and type is a number (from 1 to 4) which indicates the desired type of scatterplot (see also the figures below, for which the 'greenacre_data' dataset has been used):
-type=1: regular scatterplot for rows and columns
-type=2: Standard Biplot (2 plots are returned: one with row-categories vectors displayed, one for columns-categories vectors)
-type=3: scaterplot of row categories with groupings shown by different colors; scatterplot for column categories is also returned
-type=4: 3D scatterplot with cluster tree for row categories; scatterplot for column categories is also returned.

'chi.perm' is an R function which allows to perform the chi-square test of independence on the basis of  permuted tables, whose number is selected by user. For the rationale of this approach, see for instance the nice description provided by Beh E.J., Lombardo R. 2014, Correspondence Analysis: Theory, Practice and New Strategies, Chichester, Wiley, at pages 62-64.

'BRsim' is an R function which allows to calculate the Brainerd-Robinson similarity coefficient. Even tough it has been devised many years ago, it keeps being used in archaeological literature as even a cursory search on Google plainly shows.
The function reports:
a) a correlation matrix in tabular form, displayed on the R console;
b) a heat-map representing, in a graphical form, the aforementioned correlation matrix.
In the heat-map, the size and the color of the squares are proportional to the Brainerd-Robinson coefficients, which are also reported by numbers.

'plot.mw' is an R function which allows to perform Mann-Whitney test, and to display the test's results in a plot along with two boxplots.
The boxplots display the distribution of the values of the two samples , and jittered points represent the individual observations. At the bottom of the chart, a subtitle arranged on three lines reports relevant statistics:
-test statistic (namely, U) and the associated z and p value;
-Probability of Superiority value (which can be interpreted as an effect-size measure);
-another measure of effect size, namely r, whose thresholds are indicated in the last line of the plot's subtitle.

R function for posterior probability for relations between two Bayesian radiocarbon phases.

The function allows to calculate the posterior probability for different chronological relations between two phases defined via Bayesian radiocarbon modeling.  Obviously, for the results to make sense, the phases have to be defined as independent if one wishes to assess what is the posterior probability for different relative chronological relations between them (for the rationale, see this article by Buck et al 1992, 508-9).

""R Script to perform seriation of a contingency table by means of Correspondence Analysis.

Features
Input:
-Input data format: cross-tabulation
-Input data file format: .txt (can be easily created by means of any spreadsheet program or stats tools)
Output:
a) CA scatterplots for Dimensions 1&2, 1&3, 1&4
b) CA scatterplots (for the aforementioned dimensions) with rows and cols clustering. Cluster membership indicated by colours
c) cluster trees for rows and columns
d) seriation chart (i.e., chart representing the  contigency table seriated on the basis of the 1st CA dimension).

The Script also provides an Excel file containing relevant data and information:
-original dataset
-seriated dataset
-seriated dataset coded as presence/absence
-rows and cols CA coordinates
-rows and cols cluster membership

Video Tutorial at this link: http://www.youtube.com/watch?v=rNpscBUe-hM

""Note:
The use of the Script is described in the Journal article titled "An R Script to Facilitate Correspondence Analysis. A Guide to the Use and the Interpretation of Results from an Archaeological Perspective", to be published on Archeologia e Calcolatori.

Script features:
-data can be easily fed as a cross-tab in .txt format
-results are provided in a series of graphs, and a textual output with relevant information is provided as well
-the script returns the following charts:
--Bar chart of the strenght of the correlation between rows and columns of the input crosstab
--Bar chart of the percentage of Inertia explained by the dimensions
--Malinvaud Test Plot (note: the Script will plot only the Dimensions that are significant according to the Malinvaud Test)
--Bar charts of the Quality of the diplay of Rows and Columns categories on pairs of successive dimensions
--Bar charts of the Contribution of Row and Column categories to the Dimensions
--Bar charts of the Correlation of Row and Column categories with the Dimensions
--CA symmetric Map displaying both Row and Column points
--CA symmetric Map for Rows only
--CA symmetric Map for Columns only
--CA Standard Biplots
--2D CA Maps with clustering (for Rows)
--3D CA Map with clustering (for Rows)
--Clusters Tree with indication of group membership (for Rows)
--2D CA Maps with clustering (for Columns)
--3D CA Map with clustering (for Columns)
--Clusters Tree with indication of group membership (for Columns)

Info and download at the following link:
http://xoomer.virgilio.it/gianmarco.alberti/index_file/Page395.htm"

"Features:

‐Number of Samples handled (entered by user): 2 (up to 1000 observations)

‐Operations on entered samples:
Automatically provided: sorted sample, Trimmed sample, Winsorized sample, random sample.

‐Descriptive statistics:
Number of observations, min., max., sum, range, arithmetic mean, variance, standard deviation, mean absolute
deviation, standard error, x% confidence interval for population mean, x% lower confidence limit, x% upper
confidence limit, 1 quartile, median, 3 quartile, midspread, median absolute deviation, x% confidence interval for
population median, x% lower confidence limit, x% upper confidence limit, Tukey's trimean, skewness, kurtosis.

‐Outliers detection:
Mean, Median, Inter Quartile Range methods.

‐Hypothesis Testing:
t‐Test for independent samples: t‐Test (for the original samples), “Robust” t‐Test (for Trimmed samples, using
trimmed estimators) (+ Bullet Graphs comparing 80, 95 and 99% Confidence Interval for population Mean).
Welch’t (for both original and trimmed samples).
F‐Test for difference in variance (for both original and Trimmed samples).
Midspread comparison: for both original and Trimmed samples.
Mann‐Whitney test (+ Bullet Graphs comparing 80, 95 and 99% Confidence Interval for population Median).
Kolmogorov‐Smirnov test (for both original and Trimmed samples) (+ plot of cumulative distribution of the samples
being compared).

‐Correlation:
Pearson’s r, with confidence interval for population’s r (for both original and Trimmed samples).
Spearman’s r (for both original and Trimmed samples).
Scattergrams of Sample 1 vs Sample 2, Trimmed Sample 1 vs Trimmed Sample 2 (+ regression equation).

‐Graphics:
Box‐plots for original, trimmed, winsorized and random samples.
Box‐plots for original and trimmed samples with indication of median, mean, 1 quartile, 3 quartile, smallest&largest
non‐outlier observations.
Histograms of frequency distribution for original, trimmed, winsorized and random samples.
Histograms of frequency and cumulative distribution for original, trimmed, winsorized and random samples.
Histograms for Confidence Range of population mean for original, trimmed, winsorized and random samples.
Back‐to‐back frequency distribution histograms for original, Trimmed and random samples.
Bullet graphs for comparing 80%, 95% and 99% Confidence Range for Population Mean (for original and trimmed
samples).
Bullet graphs for comparing 80%, 95% and 99% Confidence Range for Population Median (for original and trimmed
samples).
Plot of cumulative distribution of the samples being compared.
Scattergrams of correlation between Samples."

"The template can handle data organized as a contingency table, with up to 60 rows and 20 columns.

Fisher's exact p is provided for 2x2 tables.

The template also provides the smallest fnumber expected value, and the % of expected values that are < 5. The figures should guide the user in the evaluation of the reliability of chi-square test (and, in case of 2x2 table, should inform the user wheter or not use Fisher's p vs Chi-square p).

A verbal explanation of the test's results is also provided.

The Template provides tables with:
expected values,
chi-square values
standardized residuals
p values of standardized residuals
adjusted standardized residuals
p values of adj standardazied residuals

The Template also provides:
Cohen’s w index (effect size)
Pearson's Phi
Pearson’s C
Pearson’s C adjusted
Cramer's V
Yule's Q
Goodman-Kendal's tau
-index of dispersion
-index of qualitative variation
-bar chart for chi-square residuals

One sheet provides some quick web references to topics related to the chi-sqaure test and related coefficients.

Video tutorial at this address:
http://www.youtube.com/watch?v=9Bb0ofvUIrM

""Template to perform Kruskal-Wallis Test in Excel.
It can handle up to 20 samples; each sample's size can be up to 100 observations.

Test's results:
-test statistic (H)
-test statistic corrected for ties
-p value

Post-hoc test provided: Dunn's Test for multiple pairwise comparisons.
Features:
-Bonferroni correction
-rank differences between samples
-absolute standardized rank differences
-significance of the absolute standardized differences
-effect size for samples' differences

Video tutorial at this link:
http://www.youtube.com/watch?v=eLYBDocC6bw""

Six hours of lectures (1 ECTS) on Material culture, spatial patterns, and social organization: a view from Bronze Age Aeolian archipelago and Statistics in archaeology: approaches and perspectives as a module of the course “CSAR 350 - Crossroads of Civilizations: Archaeology of Ancient Sicily”

'CAinterprTools' is a R package for visual aid to Correspondence Analysis interpretation. The package (which is described in Alberti G, CAinterprTools: An R package to help interpreting Correspondence Analysis’ results, SoftwareX, Volumes 1–2, September 2015, Pages 26-31) has been improved several times since 2015.
An updated description of the facilities it provides can be found in this technical report.

GmAMisc is a R package that collects a number of functions that I have built in different points in time. The functions' aim spans from univariate outlier detection, to permutation t test, permutation chi-square test, calculation of Brainerd-Robinson similarity coefficient, validation of logistic regression models, calculation of Posterior Probability for the chronological relations between two Bayesian radiocarbon phases, and more. The package comes with some toy datasets.

The report describes the TRANSIT ArcGIS toolbox that allows estimating the duration of sail-powered navigation from a user-defined starting location. The toolbox, its rationale, use, and application in a worked example, are fully described in the following article, which is in press: Alberti G. 2017. TRANSIT: a GIS toolbox for estimating the duration of ancient sail-powered navigation, in Cartography and Geographic Information Science (http://dx.doi.org/10.1080/15230406.2017.1403376). The toolbox (current version 0.1) is freely available from my GitHub repository: https://github.com/gianmarcoalberti/TRANSIT.

The report describes an ArcGIS toolbox that provides the facility to calculate the Fuzzy Viewshed as proposed by Ogburn 2006, which modify the original proposal by Fisher. It produces a Fuzzy Vieshed raster in which, as customary in 'regular' (i.e., binary) viewshed rasters, 0 indicates cells that are not visible, 1 indicates cells that are visible. However, unlike binary viewshed, values between 0 and 1 correspond to a drop in visibility as function of the target distance AND target size.
The toolbox can be downloaded from the link provided in the report.