locfit, gtools, caTools, pscl, Imap, RCurl, devtools, raster,
sp, rgdal, ggplot2, lattice, RColorBrewer, agricolae

The paleofire package provides tools to extract and analyse
charcoal sedimentary data stored in the Global Charcoal Database. Main
functionalities includes data extraction and sites selection,
transformation and interpolation of the charcoal records as well as
compositing.
locfit, gtools, caTools, pscl, Imap, RCurl, devtools, raster,
sp, rgdal, ggplot2, lattice, RColorBrewer, agricolae, plyr

Analysis of Charcoal Records from the Global Charcoal Database
Tools to extract and analyse charcoal sedimentary data stored in the Global
Charcoal Database. Main functionalities includes data extraction and sites selection,
transformation and interpolation of the charcoal records as well as compositing.
locfit, gtools, caTools, Imap, raster, rgdal, ggplot2,
lattice, RColorBrewer, plyr, sp, pscl, agricolae

locfit, raster, ggplot2, plyr, rgdal, lattice

Tools to extract and analyse charcoal sedimentary data stored in
the Global Charcoal Database. Main functionalities includes data extraction
and sites selection, transformation and interpolation of the charcoal
records as well as compositing.

Geometric Morphometric Tools for Paleobiology
Fill missing symmetrical data with mirroring, calculate Procrustes alignments with or without scaling, and compute standard or vector correlation and covariance matrices (congruence coefficients) of 3D landmarks. Tolerates missing data for all analyses.

Pattern-Oriented Modeling Framework for Coupled Niche-Population
Paleo-Climatic Models
c(
person("Sean", "Haythorne", email = "sean.haythorne@adelaide.edu.au", role = c("aut")),
person("Julia", "Pilowsky", email = "julia.pilowsky@adelaide.edu.au", role = c("aut", "cre"),
comment = c(ORCID = "https://orcid.org/0000-0002-6376-2585")))
This extension of the poems pattern-oriented modeling (POM) framework
provides a collection of modules and functions customized for paleontological
time-scales, and optimized for single-generation transitions and large populations,
across multiple generations.
data.R PaleoPopModel.R PaleoPopResults.R PaleoRegion.R
paleopop_simulator.R paleopop.R region_subset.R
testthat (>= 3.0.0), knitr, rmarkdown, markdown, dplyr,
raster
Sean Haythorne [aut],
Julia Pilowsky [aut, cre] (<https://orcid.org/0000-0002-6376-2585>)