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.

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

x

This required argument is an object of class `demonoid`

,
codedemonoid.hpc, `iterquad`

, `laplace`

, `pmc`

,
`vb`

, or a \(S \times J\) 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.

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.

`IterativeQuadrature`

,
`LaplaceApproximation`

,
`LaplacesDemon`

,
`LaplacesDemon.hpc`

,
`PMC`

,
`p.interval`

,
`SIR`

, and
`VariationalBayes`

.

```
# NOT RUN {
#An example is provided in the LaplacesDemon function.
# }
```

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