R: Discriminant analysis based on MCMC output from the mixture...

NMixPredDA {mixAK}

R Documentation

Discriminant analysis based on MCMC output from the mixture model

Description

It performs discriminant analysis based on sampled (re-labeled) MCMC chains from the mixture model fitted with NMixMCMC function. Observations to be discriminated may be censored.

Discrimination is based on posterior predictive probabilities of belonging to (re-labeled) mixture components.

Usage

NMixPredDA(object, y0, y1, censor, inity, info)

Arguments

`object`	an object of class `NMixMCMC`
`y0`	vector, matrix or data frame with observations (or limits of censored-observations) to be clustered. See `NMixMCMC` for details. If `y0` is not given then the function discriminates original observations used to generate MCMC sample stored in `object`.
`y1`	vector, matrix or data frame with upper limits of interval-censored observations (if there are any). See `NMixMCMC` for details.
`censor`	vector, matrix or data frame with censoring indicators (if there are any censored observations). See `NMixMCMC` for details.
`inity`	optional vector, matrix or data frame with initial values of censored observations (if there are any censored observations)
`info`	number which specifies frequency used to re-display the iteration counter during the computation.

Value

A data.frame with columns labeled prob1,..., probp giving posterior predictive probabilities of belonging to each component and a column labeled component giving the index of the component with the highest component probability.

Author(s)