blasso.s3 {monomvn} | R Documentation

## Summarizing Bayesian Lasso Output

### Description

Summarizing, printing, and plotting the contents of a `"blasso"`-class object containing samples from the posterior distribution of a Bayesian lasso model

### Usage

    ## S3 method for class 'blasso':
    print(x, ...)
    ## S3 method for class 'blasso':
    summary(object, burnin = 0, ...)
    ## S3 method for class 'blasso':
    plot(x, which=c("coef", "s2", "lambda2", "gamma",
        "tau2i","omega2", "nu", "m", "pi"), subset = NULL, burnin = 0,
        ... )
    ## S3 method for class 'summary.blasso':
    print(x, ...)

### Arguments

`object` | a `"blasso"`-class object that must be named `object` for the generic methods `summary.blasso`
`x` | a `"blasso"`-class object that must be named `x` for the generic printing and plotting methods `print.summary.blasso` and `plot.blasso`
`subset` | a vector of indicies that can be used to specify the a subset of the columns of `tau2i` or `omega2` that are plotted as boxplots in order to reduce clutter
`burnin` | number of burn-in rounds to discard before reporting summaries and making plots. Must be non-negative and less than `x$T`
`which` | indicates the parameter whose characteristics should be plotted; does not apply to the `summary`
`...` | passed to `print.blasso`, or `plot.default`

### Details

`print.blasso` prints the `call` followed by a brief summary of the MCMC run and a suggestion to try the summary and plot commands.

`plot.blasso` uses an appropriate `plot` command on the `list` entries of the `"blasso"`-class object thus visually summarizing the samples from the posterior distribution of each parameter in the model depending on the `which` argument supplied.

`summary.blasso` uses the `summary` command on the list entries of the `"blasso"`-class object thus summarizing the samples from the posterior distribution of each parameter in the model.

`print.summary.monomvn` calls `print.blasso` on the `object` and then prints the result of `summary.blasso`

### Value

`summary.blasso` returns a `"summary.blasso"`-class object, which is a `list` containing (a subset of) the items below. The other functions do not return values.

`B` | a copy of the input argument `thin`
`T` | total number of MCMC samples to be collected from `x$T`
`thin` | number of MCMC samples to skip before a sample is collected (via thinning) from `x$T`
`coef` | a joint `summary` of `x$mu` and the columns of `x$beta`, the regression coefficients
`s2` | a `summary` of `x$s2`, the variance parameter
`lambda2` | a `summary` of `x$lambda2`, the penalty parameter, when lasso or ridge regression is active
`lambda2` | a `summary` of `x$gamma`, when the NG extensions to the lasso are used
`tau2i` | a `summary` of the columns of the latent `x$tau2i` parameters when lasso is active
`omega2` | a `summary` of the columns of the latent `x$omega2` parameters when Student-t errors are active
`nu` | a `summary` of `x$nu`, the degrees of freedom parameter, when the Student-t model is active
`bn0` | the estimated posterior probability that the individual components of the regression coefficients `beta` is nonzero
`m` | a `summary` the model order `x$m`: the number of non-zero regression coefficients `beta`
`pi` | the estimated Binomial proportion in the prior for the model order when 2-vector input is provided for `mprior`

### Author(s)

Robert B. Gramacy bobby@statslab.cam.ac.uk

### References

http://www.statslab.cam.ac.uk/~bobby/monomvn.html

### See Also

`blasso`

[Package monomvn version 1.8 Index]