R: Caterpillar Plot

caterpillar.plot {LaplacesDemon} | R Documentation

## Caterpillar Plot

### Description

A caterpillar plot is a horizontal plot of 3 quantiles of selected distributions. This may be used to produce a caterpillar plot of posterior samples (parameters and monitored variables) from an object either of class `demonoid`, `demonoid.hpc`, `iterquad`, `laplace`, `pmc`, `vb`, or a matrix.

### Usage

    caterpillar.plot(x, Parms=NULL, Title=NULL)

### Arguments

`x` | This required argument is an object of class `demonoid`, codedemonoid.hpc, `iterquad`, `laplace`, `pmc`, `vb`, or a S x J matrix of S samples and J variables. For an object of class `demonoid`, the distributions of the stationary posterior summary (`Summary2`) will be attempted first, and if missing, then the parameters of all posterior samples (`Summary1`) will be plotted. For an object of class `demonoid.hpc`, stationarity may differ by chain, so all posterior samples (`Summary1`) are used. For an object of class `laplace` or `vb`, the distributions in the posterior summary, `Summary`, are plotted according to the posterior draws, sampled with sampling importance resampling in the `SIR` function. When a generic matrix is supplied, unimodal 95% HPD intervals are estimated with the `p.interval` function.
`Parms` | This argument accepts a vector of quoted strings to be matched for selecting parameters and monitored variables for plotting (though all parameters are selected when a generic matrix is supplied). This argument defaults to `NULL` and selects every parameter for plotting. Each quoted string is matched to one or more parameter names with the `grep` function. For example, if the user specifies `Parms=c("eta", "tau")`, and if the parameter names are beta[1], beta[2], eta[1], eta[2], and tau, then all parameters will be selected, because the string `eta` is within `beta`. Since `grep` is used, string matching uses regular expressions, so beware of meta-characters, though these are acceptable: ".", "[", and "]".
`Title` | This argument accepts a title for the plot.

### Details

Caterpillar plots are popular plots in Bayesian inference for summarizing the quantiles of posterior samples. A caterpillar plot is similar to a horizontal boxplot, though without quartiles, making it easier for the user to study more distributions in a single plot. The following quantiles are plotted as a line for each parameter: 0.025 and 0.975, with the exception of a generic matrix, where unimodal 95% HPD intervals are estimated (for more information, see `p.interval`). A vertical, gray line is included at zero. For all but class `demonoid.hpc`, the median appears as a black dot, and the quantile line is black. For class `demonoid.hpc`, the color of the median and quantile line differs by chain; the first chain is black and additional chains appear beneath.

### Author(s)

Statisticat, LLC. software@bayesian-inference.com

### See Also

`IterativeQuadrature`, `LaplaceApproximation`, `LaplacesDemon`, `LaplacesDemon.hpc`, `PMC`, `p.interval`, `SIR`, and `VariationalBayes`.

### Examples

    #An example is provided in the LaplacesDemon function.

[Package LaplacesDemon version 16.1.1 Index]