GaussianMixtureResponse: Generate a Gaussian Mixture Response model

In mcplR: Multiple Cue Probability Learning in R

Description

Constructs a GaussianMixtureResponse object.

Usage

GaussianMixtureResponse(formula,ncomponent=2,fixed,parStruct,data,subset,
  weights,ntimes=NULL,replicate=TRUE)

Arguments

formula	an object of class formula (or one that can be coerced to that class): a symbolic description of the model to be fitted. For more details of model specification, see lm or glm.
ncomponent	number of mixture components.
fixed	a logical vector indicating whether model parameters are fixed or free
parStruct	a ParStruct object. If supplied, the fixed argument above will be ignored
data	(optional) data frame.
subset	(optional) subset.
weights	(optional) mixture weights.
ntimes	an optional vector with, for each repetition in the data, the total number of trials.
replicate	logical to indicate whether model parameters are identical for each replication in ntimes.

Details

The GaussianMixtureResponse function sets up a simple Normal finite mixture model.

Value

A (fitted) object of class GaussianMixtureResponse.

mcplR documentation built on May 2, 2019, 4:42 p.m.