update: Update and refit an 'ouch' model

Description Usage Arguments Value See Also

Description

update will update a model and re-fit. This allows one to change the data and/or parameters.

Usage

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## S4 method for signature 'browntree'
update(object, data, ...)

## S4 method for signature 'hansentree'
update(object, data, regimes, sqrt.alpha, sigma, ...)

Arguments

object

fitted model object.

data

data that replace those used in the original fit.

...

Additional arguments replace the corresponding arguments in the original call.

regimes

A vector of codes, one for each node in the tree, specifying the selective regimes hypothesized to have been operative. Corresponding to each node, enter the code of the regime hypothesized for the branch segment terminating in that node. For the root node, because it has no branch segment terminating on it, the regime specification is irrelevant. If there are nchar quantitative characters, then one can specify a single set of regimes for all characters or a list of nchar regime specifications, one for each character.

sqrt.alpha

These are used to initialize the optimization algorithm. The selection strength matrix alpha and the random drift variance-covariance matrix sigma^2 are parameterized by their matrix square roots. Specifically, these initial guesses are each packed into lower-triangular matrices (column by column). The product of this matrix with its transpose is the alpha or sigma^2 matrix. See Details for more information.

sigma

These are used to initialize the optimization algorithm. The selection strength matrix alpha and the random drift variance-covariance matrix sigma^2 are parameterized by their matrix square roots. Specifically, these initial guesses are each packed into lower-triangular matrices (column by column). The product of this matrix with its transpose is the alpha or sigma^2 matrix. See Details for more information.

Value

update returns a new fitted-model object of the same class as object.

See Also

Other methods for ouch trees: bootstrap(), coef(), logLik, ouch-package, paint(), plot(), print(), simulate(), summary()


ouch documentation built on May 17, 2021, 1:09 a.m.

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