mlsmu6: MLSMU6

In davidaarmstrong/asmcjr: Analyzing Spatial Models of Choice and Judgment with R

MLSMU6

Description

Metric unfolding using the MSLMU6 algorithm.

Usage

mlsmu6(input, ndim=2, cutoff=5, tol=0.0005, maxit=50, id=NULL)

Arguments

input	An data frame or matrix of individuals by stimuli placements.
ndim	Number of latent dimensions to be generated.
cutoff	Minimum number of stimuli that need to be rated to be included in result.
tol	Tolerance to identify convergence on the aggregate sum of squared errors.
maxit	Maximum number of iterations permitted
id	Optional vector of identifiers (e.g., party labels) for the individuals.

Value

A list that will include the following:

stims	A number of stimuli by number of dimensions matrix of scaled stimulus values.
inds	A number of individuals by number of dimensions matrix of scaled individual values.
iter	Iteration history.

davidaarmstrong/asmcjr documentation built on June 29, 2024, 12:07 p.m.