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| paleoTS-package | Analysis of evolutionary time-series |
| akaike.wts | Compute information criterion scores and Akaike weights for evoltuionary models |
| as.paleoTS | Paleontological time-series class |
| as.paleoTSfit | Class for fit to paleontological time-series models |
| bootSimpleComplex | Use parametric bootstrapping to test the fit of a complex model relative to a simpler one |
| cat.paleoTS | Miscellaneous functions used internally for punctuations |
| compareModels | Compare output from any set of model fits |
| dorsal.spines | Stickleback data from Bell et al. (2006) |
| ESD | Compute Expected Squared Divergence (ESD) for simple evolutionary models |
| fit.sgs | Analyze evolutionary models with well-sampled punctuations |
| fit3models | Do model fits for standard sets of evolutionary models |
| fit4models | Do model fits for standard sets of evolutionary models |
| fit9models | Do model fits for standard sets of evolutionary models |
| fitGpunc | Analyze evolutionary models with unsampled punctuations |
| fitModeShift | Fit models in which start in Stasis, and then shift to a random walk (or vice versa) |
| fitMult | Functions to estimate models over multiple time-series |
| fitSimple | Fit simple models of trait evolution |
| IC | Compute information criterion scores and Akaike weights for evoltuionary models |
| ln.paleoTS | Log transform paleontological time series data |
| logL.covTrack | Covariate-tracking model |
| logL.GRW | Compute log-likelihoods for random walk and stasis models |
| logL.joint.covTrack | Covariate-tracking model |
| logL.joint.GRW | Log-likelihoods for evolutionary models (joint parameterization) |
| logL.joint.GRW.Stasis | Fit models in which start in Stasis, and then shift to a random walk (or vice versa) |
| logL.joint.Mult | Functions to estimate models over multiple time-series |
| logL.joint.OU | Log-likelihoods for evolutionary models (joint parameterization) |
| logL.joint.punc | Analyze evolutionary models with unsampled punctuations |
| logL.joint.punc.omega | Analyze evolutionary models with unsampled punctuations |
| logL.joint.Stasis | Log-likelihoods for evolutionary models (joint parameterization) |
| logL.joint.Stasis.GRW | Fit models in which start in Stasis, and then shift to a random walk (or vice versa) |
| logL.joint.Stasis.URW | Fit models in which start in Stasis, and then shift to a random walk (or vice versa) |
| logL.joint.StrictStasis | Log-likelihoods for evolutionary models (joint parameterization) |
| logL.joint.URW | Log-likelihoods for evolutionary models (joint parameterization) |
| logL.joint.URW.Stasis | Fit models in which start in Stasis, and then shift to a random walk (or vice versa) |
| logL.Mult | Functions to estimate models over multiple time-series |
| logL.Mult.covTrack | Covariate-tracking model |
| logL.Mult.joint.covTrack | Covariate-tracking model |
| logL.punc | Analyze evolutionary models with unsampled punctuations |
| logL.punc.omega | Analyze evolutionary models with unsampled punctuations |
| logL.SameMs | Functions to estimate models over multiple time-series |
| logL.SameVs | Functions to estimate models over multiple time-series |
| logL.sgs | Analyze evolutionary models with well-sampled punctuations |
| logL.sgs.omega | Analyze evolutionary models with well-sampled punctuations |
| logL.Stasis | Compute log-likelihoods for random walk and stasis models |
| logL.StrictStasis | Compute log-likelihoods for random walk and stasis models |
| logL.URW | Compute log-likelihoods for random walk and stasis models |
| LRI | Log-Rate, Log-Interval (LRI) method of Gingerich |
| 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 |
| modelCurves | Function computes model expectations and 95 |
| opt.AD.RW.Stasis | Fit models in which start in Stasis, and then shift to a random walk (or vice versa) |
| opt.AD.Stasis.RW | Fit models in which start in Stasis, and then shift to a random walk (or vice versa) |
| opt.covTrack | Covariate-tracking model |
| opt.covTrack.Mult | Covariate-tracking model |
| opt.GRW | Numerically find maximum likelihood solutions to evolutionary models |
| opt.GRW.shift | Functions for random walks with shifting parameters |
| opt.joint.covTrack | Covariate-tracking model |
| opt.joint.covTrack.Mult | Covariate-tracking model |
| opt.joint.GRW | Optimize evolutionary models (joint parameterization) |
| opt.joint.Mult | Functions to estimate models over multiple time-series |
| opt.joint.OU | Optimize evolutionary models (joint parameterization) |
| opt.joint.punc | Analyze evolutionary models with unsampled punctuations |
| opt.joint.RW.Stasis | Fit models in which start in Stasis, and then shift to a random walk (or vice versa) |
| opt.joint.Stasis | Optimize evolutionary models (joint parameterization) |
| opt.joint.Stasis.RW | Fit models in which start in Stasis, and then shift to a random walk (or vice versa) |
| opt.joint.StrictStasis | Optimize evolutionary models (joint parameterization) |
| opt.joint.URW | Optimize evolutionary models (joint parameterization) |
| opt.Mult | Functions to estimate models over multiple time-series |
| opt.punc | Analyze evolutionary models with unsampled punctuations |
| opt.RW.SameMs | Functions to estimate models over multiple time-series |
| opt.RW.SameVs | Functions to estimate models over multiple time-series |
| opt.sgs | Analyze evolutionary models with well-sampled punctuations |
| opt.Stasis | Numerically find maximum likelihood solutions to evolutionary models |
| opt.StrictStasis | Numerically find maximum likelihood solutions to evolutionary models |
| opt.URW | Numerically find maximum likelihood solutions to evolutionary models |
| ou.M | Simulate evolutionary time-series |
| ou.V | Simulate evolutionary time-series |
| paleoTS | Analysis of evolutionary time-series |
| pelvic.score | Stickleback data from Bell et al. (2006) |
| plot.paleoTS | Plots paleoTS objects |
| pool.var | Variance heterogeneity test |
| pterygiophores | Stickleback data from Bell et al. (2006) |
| read.paleoTS | Paleontological time-series class |
| shift2gg | Miscellaneous functions used internally for punctuations |
| shifts | Miscellaneous functions used internally for punctuations |
| sim.covTrack | Simulate time-series that tracks a covariate |
| sim.GRW | Simulate evolutionary time-series |
| sim.GRW.shift | Simulate evolutionary time-series with changing dynamics |
| sim.OU | Simulate evolutionary time-series |
| sim.punc | Simulate evolutionary time-series with changing dynamics |
| sim.sgs | Simulate evolutionary time-series with changing dynamics |
| sim.Stasis | Simulate evolutionary time-series |
| split4punc | Miscellaneous functions used internally for punctuations |
| std.paleoTS | Standardize paleontological time series data |
| sub.paleoTS | Subset an evolutionary time series |
| test.var.het | Variance heterogeneity test |