bestmodel: Best model, Partition, and MLE

In psolymos/opticut: Likelihood Based Optimal Partitioning and Indicator Species Analysis

Best model, Partition, and MLE

Description

Generic functions for accessing best model, best partition, and Maximum Likelihood Estimate from fitted objects.

Usage

bestmodel(object, ...)
bestpart(object, ...)
getMLE(object, ...)

Arguments

object	fitted model object.
...	other arguments passed to the underlying functions.

Value

bestmodel returns the best supported model for further manipulation (e.g. prediction).

bestpart returns a matrix with the best supported partitions for each species (species as columns).

getMLE returns a named list corresponding to the best supported model. The list has the following elements: coef is the Maximum Likelihood Estimate (MLE), vcov is the variance-covariance matrix for the MLE, dist is the distribution inherited from input object.

Author(s)

Peter Solymos <[e-mail]>

See Also

opticut, multicut, uncertainty.

psolymos/opticut documentation built on Nov. 27, 2022, 11:29 a.m.