R: trace plot of MCMC iterates, posterior density of...

tracex {pscl} | R Documentation

## trace plot of MCMC iterates, posterior density of legislators' ideal points

### Description

Produces a trace plot of the MCMC samples from the posterior density of legislators' `ideal` points.

### Usage

    tracex(object, legis=NULL, d=1, conf.int=0.95,
           multi = FALSE, burnin=NULL,span=.25,
           legendLoc="topright")

### Arguments

`object` | an object of class `ideal`.
`legis` | a vector of either the names of legislators (or `partial matches` of the names as given in the `dimnames` of `object$x`.
`d` | numeric, either a scalar or a vector of length two, the dimension(s) to be traced.
`conf.int` | numeric, the level of the confidence interval on the posterior mean to be plotted.
`multi` | logical, multiple plotting panels, one per legislators? If `FALSE` (default) and `length(d)==2`, display traces for all selected legislators' ideal points on the one plot.
`burnin` | of the recorded MCMC samples, how many to discard as burnin? Default is `NULL`, in which case the value of `burnin` in the `ideal` object is used.
`span` | numeric, a proportion, the `span` to be used when calling `loess` to generate a moving average for trace plots when `d=1`
`legendLoc` | numeric or character, and possibly a vector, specifying where to place the legend when `d=1`; setting `legendLoc=NULL` will suppress the legend for all requested trace plots

### Details

Produces a trace plot showing the history of the MCMC iterations for the ideal point of each of the legislators (partially) named in `legis`. For `d=1`, each trace plot includes a trace over iterations, the cumulative mean, a moving average, the MCMC-based estimate of the mean of the posterior, and a confidence interval (specified by `conf.int`) around the mean of the posterior (using the estimated `quantiles`) of the respective MCMC iterates). All of these values are calculated discarding the initial `burnin` iterations.

When `d` is a vector of length two, a 2-dimensional trace plot is displayed, with the `d[1]` dimension on the horizontal axis, and the `d[2]` dimension on the vertical axis.

When `d=1`, a legend will be placed on the plot; the option `legendLoc` controls the placing of the legend. `legendLoc` may be a vector, specifying a unique legend location for each requested trace plots. If `legendLoc` is of length 1, it will be `rep`licated to have length equal to the number of requested trace plots.

### See Also

`ideal`; `pmatch` for matching legislators' names. See `legend` for valid options to `legendLoc`.

### Examples

    data(s109)
    f <- system.file("extdata","id1.rda",package="pscl")
    load(f)
    tracex(id1,legis="KENN")

    ## n.b., no such legislator named Thomas Bayes
    tracex(id1,legis=c("KENN","BOX","KYL","Thomas Bayes"))

    f <- system.file("extdata","id2.rda",package="pscl")
    load(f)

    tracex(id2,d=1,legis=c("KENNEDY","BOXER","KYL","Thomas Bayes"))
    tracex(id2,d=2,legis=c("KENNEDY","BOXER","KYL","Thomas Bayes"))
    tracex(id2,d=1:2,
           legis=c("KENNEDY","BOXER","KYL","Thomas Bayes"))

    ## partial matching
    tracex(id2,d=1:2,
           legis=c("KENN","BOX","BID","SNO","SPEC","MCCA","KYL",
                   "Thomas Bayes"),
           multi=TRUE)

[Package pscl version 1.5.2 Index]