dfzinbt: Discrete factor analysis with the zero inflated truncated...

In discFA: Discrete Factor Analysis

Discrete factor analysis with the zero inflated truncated negative binomial distribution.

Description

Discrete factor analysis with the zero inflated truncated negative binomial distribution.

Usage

dfzinbt(y, A, tol = 1e-06)

Arguments

y	Data, an n by d numeric matrix
A	truncation point (Note that if the data is in Likert scale starting from 1, then you should subtract 1 from the data and then use the proposed negative binomial models.
tol	tolerance value for optimizations

Value

A list with entries.

AIC	AIC value for the optimal model
indexmat	Factors and variables in each factor
estpi0	Estimated value of p for the zero inflated part in the negative binomial distributed factor
estr0	Estimated value of r the negative binomial distributed factor(s)
estp0	Estimated value of p the negative binomial distributed factor(s)
estpi	Estimated parameters for the zero inflated part in the negative binomial distributed observations(s)
estr	Estimated value of r negative binomial distributed observations(s)
estp	Estimated value of p negative binomial distributed observations(s)

Examples

dfzinbt(zinb100_Data[1:20,1:3], A = 6)

discFA documentation built on May 29, 2024, 3:11 a.m.