Other packages > Find by keyword >

BaSkePro  

Bayesian Model to Archaeological Faunal Skeletal Profiles
View on CRAN: Click here


Download and install BaSkePro package within the R console
Install from CRAN:
install.packages("BaSkePro")

Install from Github:
library("remotes")
install_github("cran/BaSkePro")

Install by package version:
library("remotes")
install_version("BaSkePro", "1.1.1")



Attach the package and use:
library("BaSkePro")
Maintained by
Marco Vidal-Cordasco
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-02-17
Latest Update: 2024-01-10
Description:
Tool to perform Bayesian inference of carcass processing/transport strategy and bone attrition from archaeofaunal skeletal profiles characterized by percentages of MAU (Minimum Anatomical Units). The approach is based on a generative model for skeletal profiles that replicates the two phases of formation of any faunal assemblage: initial accumulation as a function of human transport strategies and subsequent attrition.Two parameters define this model: 1) the transport preference (alpha), which can take any value between - 1 (mostly axial contribution) and 1 (mostly appendicular contribution) following strategies constructed as a function of butchering efficiency of different anatomical elements and the results of ethnographic studies, and 2) degree of attrition (beta), which can vary between 0 (no attrition) and 10 (maximum attrition) and relates the survivorship of bone elements to their maximum bone density. Starting from uniform prior probability distribution functions of alpha and beta, a Monte Carlo Markov Chain sampling based on a random walk Metropolis-Hasting algorithm is adopted to derive the posterior probability distribution functions, which are then available for interpretation. During this process, the likelihood of obtaining the observed percentages of MAU given a pair of parameter values is estimated by the inverse of the Chi2 statistic, multiplied by the proportion of elements within a 1 percent of the observed value. See Ana B. Marin-Arroyo, David Ocio (2018)..
How to cite:
Marco Vidal-Cordasco (2022). BaSkePro: Bayesian Model to Archaeological Faunal Skeletal Profiles. R package version 1.1.1, https://cran.r-project.org/web/packages/BaSkePro. Accessed 07 Oct. 2026.
Previous versions and publish date:
0.1.0 (2022-02-17 20:42), (2026-07-09 07:58)
Other packages that cited BaSkePro R package
View BaSkePro citation profile
Other R packages that BaSkePro depends, imports, suggests or enhances
Complete documentation for BaSkePro
Functions, R codes and Examples using the BaSkePro R package
Some associated functions: BaSkePro_description . 
Some associated R codes: BaSkePro.4.R .  Full BaSkePro package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

skewlmm  
Scale Mixture of Skew-Normal Linear Mixed Models
It fits scale mixture of skew-normal linear mixed models using an expectation–maximization (EM) ty ...
Download / Learn more Package Citations See dependency  
splm  
Econometric Models for Spatial Panel Data
ML and GM estimation and diagnostic testing of econometric models for spatial panel data. ...
Download / Learn more Package Citations See dependency  
blandr  
Bland-Altman Method Comparison
Carries out Bland Altman analyses (also known as a Tukey mean-difference plot) as described by JM B ...
Download / Learn more Package Citations See dependency  
PairedData  
Paired Data Analysis
Many datasets and a set of graphics (based on ggplot2), statistics, effect sizes and hypothesis test ...
Download / Learn more Package Citations See dependency  
ggTimeSeries  
Time Series Visualisations Using the Grammar of Graphics
Provides additional display mediums for time series visualisations. ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  

28,905

R Packages

247,686

Dependencies

76,495

Author Associations

28,906

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA