plot.elrm: Plot Diagnostics for an elrm Object
In elrm: Exact Logistic Regression via MCMC

Description Usage Arguments Details Value Author(s) References See Also Examples

Produces both a trace plot and histogram of the sampled values of each sufficient statistic of interest. Sampled values within the burn-in period are also plotted.

1 2	## S3 method for class 'elrm' plot(x, p = 1, breaks = "Sturges", ask=FALSE, ...)

`x`	an object of class `elrm`, resulting from a call to `elrm()` or a previous call to `update()`.
`p`	the sampling fraction of points to be plotted. A random sample consisting of `p`*100% of all the observations in the Markov chain is plotted; default=1.
`breaks`	a vector giving the number of cells to use for the histogram of each sufficient statistic of interest or a single number giving the number of cells for each histogram or the character string naming an algorithm to compute the number of cells.
`ask`	the graphics parameter `ask`: see `par` for details. If set to TRUE will ask between plots corresponding to each sufficient statistic; default=FALSE.
`...`	additional arguments to the plot function (currently unused).

The default for breaks is "Sturges": see nclass.Sturges. Other names for which algorithms are supplied are "Scott" and "FD".

No return value. Creates a plot of the sampled sufficent statistics for each parameter of interest.

David Zamar, Jinko Graham, Brad McNeney

Zamar, D., McNeney, B., & Graham, J. (2007). elrm: Software Implementing Exact-Like Inference for Logistic Regression Models. Journal of Statistical Software, 21(3), 1-18.

Zamar, D., Monte Carlo Markov Chain Exact Inference for Binomial Regression Models. Master's thesis, Statistics and Actuarial Sciences, Simon Fraser University, 2006

Forster, J.J., McDonald, J.W. & Smith, P.W.F. Markov chain Monte Carlo exact inference for binomial and multinomial logistic regression models. Statistics and Computing 13, 169-177 (2003).

Geyer, C.J. Practical Markov chain Monte Carlo. Statistical Science, 7:473-511, 1992

update.elrm, summary.elrm, elrm.

# Drug dataset example with treatment as the variables of interest
data(drugDat);
drug.elrm = elrm(formula=recovered/n~sex+treatment, interest=~treatment, r=4, 
	iter=2000, burnIn=100, dataset=drugDat);

# Plot the sampled values of the sufficient statistic for the parameter(s) of 
# interest
plot(drug.elrm,p=0.10,ask=TRUE);