Modeling evolution in paleontological time-series

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Documentation for package ‘paleoTS’ version 0.2-1

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paleoTS-package Analysis of evoltuionary time-series
akaike.wts Compute information criterion scores and Akaike weights for evoltuionary models
as.paleoTS Paleontological time-series class
fit3models Do model fits for three evolutionary models
IC Compute information criterion scores and Akaike weights for evoltuionary models
ln.paleoTS Log transform paleontological time series data
logL.GRW Compute log-likelihoods for random walk and stasis models
logL.Mult Functions to analyze multiple time-series jointly
logL.SameMs Functions to analyze multiple time-series jointly
logL.SameVs Functions to analyze multiple time-series jointly
logL.Stasis Compute log-likelihoods for random walk and stasis models
logL.URW Compute log-likelihoods for random walk and stasis models
lynchD Compute rate metric from Lynch (1990)
mle.GRW Maximum likelihood parameter estimators
mle.Stasis Maximum likelihood parameter estimators
mle.URW Maximum likelihood parameter estimators
opt.GRW Numerically find maximum likelihood solutions to evolutionary models
opt.RW.Mult Functions to analyze multiple time-series jointly
opt.RW.SameMs Functions to analyze multiple time-series jointly
opt.RW.SameVs Functions to analyze multiple time-series jointly
opt.Stasis Numerically find maximum likelihood solutions to evolutionary models
opt.URW Numerically find maximum likelihood solutions to evolutionary models
paleoTS Analysis of evoltuionary time-series
plot.paleoTS Plots paleoTS objects
pool.var Variance heterogeneity test
read.paleoTS Paleontological time-series class
sim.GRW Simulate evolutionary time-series
sim.Stasis Simulate evolutionary time-series
std.paleoTS Standardize paleontological time series data
sub.paleoTS Subset an evolutionary time series
test.var.het Variance heterogeneity test