Fits of multivariate evolutionary models on trees (with one or multiple selective regimes) and time-series dedicated to morphometrics or biometric continuous data with covariation. Testing for a phylogenetic signal in a multivariate dataset (including fossil and/or extant taxa), changes in rate or mode of evolution of continuous traits, simulating multivariate traits evolution, computing the likelihood of multivariate models, accounts for measurement errors and missing data, and other things...
This function allows computing the log-likelihood and estimating ancestral states of an arbitrary tree or variance-covariance matrix with differents algorithms based on GLS (Generalized Least Squares) or Independent Contrasts. Works for univariate or multivariate models. Can be wrapped for maximizing the log-likelihood of user-defined models.
This function allows simulating multivariate (as well as univariate) continuous traits evolving according to a BM (Brownian Motion), OU (Ornstein-Uhlenbeck), ACDC (Accelerating rates and Decelerating rates/Early bursts), or SHIFT models of phenotypic evolution.
This function allows the fitting of a multivariate Ornstein-Uhlenbeck (OU) model to a time series. Species measurement errors or dispersions can also be included in the model.
● Data Source:
CranContrib
● Keywords: Hessian, OU, Ornstein Uhlenbeck, Time series
● Alias: mvOUTS
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This function allows the fitting of a multivariate Ornstein-Uhlenbeck (OU) model by allowing a given tree branch to be subdivided into multiple selective regimes using SIMMAP-like mapping of ancestral states. Species measurement errors or dispersions can also be included in the model.
This function allows the fitting of multivariate multiple rates of evolution under a Brownian Motion model. This function can also fit constrained models.
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