MultiscaleModelSelection: Model selection for fitted multiscale models

In dpwynne/mmnst: Multiscale Modeling of Neural Spike Trains

Model selection for fitted multiscale models

Description

Finds the simplest multiscale model within a given tolerance of the "optimal" model as computed by an information criterion.

Usage

MultiscaleModelSelection(K.list)

Arguments

K.list

a list containing eta/gamma estimates and model fit criteria for each fitted model.

Value

A list of length 3. The first item in the list is a character vector containing the names of the best model(s). The second item in the list is a numeric vector containing the indices of the best model(s) in the list of models. The third item in the list is a data frame containing the best model for each spike train analyzed by each fit criterion.

dpwynne/mmnst documentation built on Aug. 1, 2023, 8:08 a.m.