MCMCpack: topmodels – R documentation

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topmodels

Shows an ordered list of the most frequently visited models sampled during quantile regression stochastic search variable selection (QR-SSVS).

Description

Given output from quantile regression stochastic search variable selection, this function returns a table of the 'best' models together with their associated empirical posterior probability.

Usage

topmodels(qrssvs, nmodels = 5, abbreviate = FALSE, minlength = 3)

Arguments

`qrssvs`	An object of class `qrssvs`. Typically this will be the `gamma` component of the list returned by `SSVSquantreg`.
`nmodels`	The number of models to tabulate.
`abbreviate`	Logical: should the names of the predictors be abbreviated?
`minlength`	If `abbreviate` is set to `TRUE`, the minimum length of the abbreviations.

Value

A table with the models and their associated posterior probability. The models are arranged in descending order of probability.

Author(s)

Craig Reed

Examples

## Not run: 
set.seed(1)
epsilon<-rnorm(100)
set.seed(2)
x<-matrix(rnorm(1000),100,10)
y<-x[,1]+x[,10]+epsilon
qrssvs<-SSVSquantreg(y~x)
topmodels(qrssvs$gamma)

## End(Not run)

MCMCpack

Markov Chain Monte Carlo (MCMC) Package

v1.5-0

GPL-3

Authors

Andrew D. Martin [aut], Kevin M. Quinn [aut], Jong Hee Park [aut,cre], Ghislain Vieilledent [ctb], Michael Malecki[ctb], Matthew Blackwell [ctb], Keith Poole [ctb], Craig Reed [ctb], Ben Goodrich [ctb], Ross Ihaka [cph], The R Development Core Team [cph], The R Foundation [cph], Pierre L'Ecuyer [cph], Makoto Matsumoto [cph], Takuji Nishimura [cph]

Initial release

2021-01-19