Package: paleoTS 0.6.2

Gene Hunt

paleoTS: Analyze Paleontological Time-Series

Facilitates analysis of paleontological sequences of trait values. Functions are provided to fit, using maximum likelihood, simple evolutionary models (including unbiased random walks, directional evolution,stasis, Ornstein-Uhlenbeck, covariate-tracking) and complex models (punctuation, mode shifts).

Authors:Gene Hunt [aut, cre, cph], John Fricks [ctb]

paleoTS_0.6.2.tar.gz
paleoTS_0.6.2.zip(r-4.7)paleoTS_0.6.2.zip(r-4.6)paleoTS_0.6.2.zip(r-4.5)
paleoTS_0.6.2.tgz(r-4.6-any)paleoTS_0.6.2.tgz(r-4.5-any)
paleoTS_0.6.2.tar.gz(r-4.7-any)paleoTS_0.6.2.tar.gz(r-4.6-any)
paleoTS_0.6.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
paleoTS/json (API)
NEWS

# Install 'paleoTS' in R:
install.packages('paleoTS', repos = c('https://phylotastic.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • cantius_L - Time-series of the length of lower first molar for the Cantius lineage
  • dorsal.spines - Time-series of dorsal spine data from a fossil stickleback lineage

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5.49 score 1 stars 2 packages 206 scripts 393 downloads 5 mentions 59 exports 5 dependencies

Last updated from:6fbc4f6fa3. Checks:9 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK124
source / vignettesOK183
linux-release-x86_64OK110
macos-release-arm64OK83
macos-oldrel-arm64OK87
windows-develOK88
windows-releaseOK85
windows-oldrelOK75
wasm-releaseOK100

Exports:akaike.wtsas.paleoTSas.paleoTSfitbootSimpleComplexcheckSSMresidualscompareModelsESDfit.sgsfit3modelsfit4modelsfit9modelsfitGpuncfitModeShiftfitMultfitSimpleICKfiltertvln.paleoTSLRIlynchDmle.GRWmle.Stasismle.URWopt.covTrackopt.GRWopt.GRW.shiftopt.joint.covTrackopt.joint.GRWopt.joint.OUopt.joint.puncopt.joint.Stasisopt.joint.StrictStasisopt.joint.URWopt.puncopt.ssm.ACDCopt.ssm.covOUopt.ssm.covOU_vshiftopt.ssm.GRWopt.ssm.OUopt.ssm.Stasisopt.ssm.StrictStasisopt.ssm.URWopt.ssm.URWshiftopt.Stasisopt.StrictStasisopt.URWpool.varread.paleoTSsim.covTracksim.GRWsim.GRW.shiftsim.OUsim.puncsim.sgssim.Stasissim.Stasis.RWstd.paleoTSsub.paleoTStest.var.het

Dependencies:codetoolsdoParallelforeachiteratorsmnormt

Basics of paleoTS

Gene Hunt

Rendered frompaleoTS_basics.Rmdusingknitr::rmarkdownon May 24 2026.

Last update: 2024-06-07
Started: 2019-03-12

Readme and manuals

Help Manual

Help pageTopics
Compute Akaike weights from AIC scoresakaike.wts
Make a Paleontological Time-series objectas.paleoTS
Create a 'paleoTSfit' objectas.paleoTSfit
Bootstrap test to see if a complex model is significantly better than a simple model.bootSimpleComplex
Time-series of the length of lower first molar for the Cantius lineagecantius_L
Compute and (optionally) plot residuals from SSM model fitcheckSSMresiduals
Compare model fits for a paleontological time-seriescompareModels
Time-series of dorsal spine data from a fossil stickleback lineagedorsal.spines
Compute Expected Squared Divergence (ESD) for Evolutionary ModelsESD
Fit a model of trait evolution with a protracted punctuation.fit.sgs
Fit a set of standard evolutionary modelsfit3models fit4models
Fit large set of models to a time-seriesfit9models
Fit trait evolution model with punctuations estimated from the datafitGpunc
Fit model in which the mode of trait evolution shifts oncefitModeShift
Fit the same simple model across multiple time-seriesfitMult
Fit simple models of trait evolutionfitSimple
Compute Information CriteriaIC
Time-varying Kalman filter calculationsKfiltertv
Approximate log-transformation of time-series dataln.paleoTS
Log-rate, Log-interval (LRI) method of GingerichLRI
Compute Lynch's Delta rate metriclynchD
Analytical ML estimator for random walk and stasis modelsmle.GRW mle.Stasis mle.URW
Fit a model in which a trait tracks a covariateopt.covTrack opt.joint.covTrack
Fit evolutionary model using "AD" parameterizationopt.GRW opt.Stasis opt.StrictStasis opt.URW
Fit random walk model with shift(s) in generating parametersopt.GRW.shift
Fit evolutionary models using the "Joint" parameterizationopt.joint.GRW opt.joint.Stasis opt.joint.StrictStasis opt.joint.URW
Fit Ornstein-Uhlenbeck model using the "Joint" parameterizationopt.joint.OU
Fit a model of trait evolution with specified punctuation(s)opt.joint.punc opt.punc
Fit evolutionary models using state-space models (SSM)opt.ssm.ACDC opt.ssm.covOU opt.ssm.covOU_vshift opt.ssm.GRW opt.ssm.OU opt.ssm.Stasis opt.ssm.StrictStasis opt.ssm.URW opt.ssm.URWshift
Plot a paleoTS objectplot.paleoTS
Compute a pooled variancepool.var
Print a paleoTSfit objectprint.paleoTSfit
Read a text-file with data from a paleontological time-seriesread.paleoTS
Simulate trait evolution that tracks a covariatesim.covTrack
Simulate random walk or directional time-series for trait evolutionsim.GRW
Simulate (general) random walk with shift(s) in generating parameterssim.GRW.shift
Simulate an Ornstein-Uhlenbeck time-seriessim.OU
Simulate a punctuated time-seriessim.punc
Simulate protracted punctuationsim.sgs
Simulate Stasis time-series for trait evolutionsim.Stasis
Simulate trait evolution with a mode shiftsim.Stasis.RW
Convert time-series to standard deviation unitsstd.paleoTS
Subsample a paleontological time-seriessub.paleoTS
Test for heterogeneity of variances among samples in a time-seriestest.var.het