Packaged: Fri Aug  8 10:24:53 2008; david

Packaged: Mon Jan 26 13:16:48 2009; david

Description: Contains functions for the analysis of Discrete Time
Hidden Markov Models, Markov Modulated GLMs and the Markov
Modulated Poisson Process. It includes functions for
simulation, parameter estimation, and the Viterbi algorithm.
See the topic "HiddenMarkov" for an introduction to the
package, and "Changes" for a list of recent changes. The
algorithms are based of those of Walter Zucchini.

Description: Contains functions for the analysis of Discrete Time Hidden Markov Models, Markov Modulated GLMs and the Markov Modulated Poisson Process. It includes functions for simulation, parameter estimation, and the Viterbi algorithm. See the topic "HiddenMarkov" for an introduction to the package, and "Change Log" for a list of recent changes. The algorithms are based of those of Walter Zucchini.

Title: Partitioning Hierarchical Diversity and Differentiation Across
Metrics and Scales, from Genes to Ecosystems
Description: Miscellaneous R functions for calculating and decomposing multiple hierarchical diversity metrics, including hierarchical allele richness (q=1), hierarchical exponential Shannon entropy (q=1), hierarchical heterozygosity (q=2) and genetic differentiation (Fst and Delta D). This package allows you to analyse spatial structured genetic data or species data under a unifying framework (Gaggiotti, O. E. et al, 2018, Evol Appl, 11:1176-1193; <DOI:10.1111/eva.12593>), which partitions diversity and differentiation into any hierarchical levels. It helps you easily structure and format your data. It produces diversity profiles (q=0,1,2), hierarchical diversities and differentiation, as well as the the correlation between geographic distance and genetic differentiation.
Imports: GGally, adegenet, diveRsity, dplyr, entropart, ggplot2,

Description: Miscellaneous R functions for calculating and decomposing hierarchical diversity metrics, including hierarchical allele richness (q=0), hierarchical exponential Shannon entropy (q=1), hierarchical heterozygosity (q=2) and genetic differentiation (Fst and Delta D). This package allows you to analyse spatial structured genetic data or species data under a unifying framework (Gaggiotti, O. E. et al, 2018, Evol Appl, 11:1176-1193; <DOI:10.1111/eva.12593>), which partitions diversity and differentiation into any hierarchical levels. It helps you easily structure and format your data. It produces diversity profiles (q=0,1,2), hierarchical diversities and differentiation, as well as the the correlation between geographic distance and genetic differentiation.