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 |

`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 |

`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.`

*LaplacesDemon*version 16.1.6 Index]