Analyze Paleontological Time-Series.
paleoTS
The goal of paleoTS is to allow the user to simulate and fit time-series models commonly used to understand trait evolution in paleontology. Models include random walks, stasis, directional trends, OU, covariate-tracking, punctuations and more. Model fitting is done via maximum likelihood.
Example
This is a simple example in which a time-series is generated, plotted, and then fit with three common models in paleobiology. The generating model is a general (also called biased) random walk, with a pretty strong trend parameter. Usually, this model receives just about all of the available model support with these generating parameters.
library(paleoTS)
y <- sim.GRW(ns = 40, ms = 0.3)
plot(y)
fit3models(y)
#>
#> Comparing 3 models [n = 40, method = Joint]
#>
#> logL K AICc dAICc Akaike.wt
#> GRW -26.71456 3 60.09579 0.00000 0.998
#> URW -34.09895 2 72.52223 12.42644 0.002
#> Stasis -106.97466 2 218.27365 158.17785 0.000
Take a look at the vignette “paleoTS_basics” for more of an introduction to this package.
Installation
paleoTS should be installed from CRAN.