stanDxplot

an <code>rms</code> Bayesian fit object

names of parameters to plot, defaulting to all non-intercepts. When <code>rstan=FALSE</code> these are the friendly <code>rms</code> names, otherwise they are the <code>rstan</code> parameter names. If the model fit was run through <code>stackMI</code> for multiple imputation, the number of traces is multiplied by the number of imputations. Set to <code>'ALL'</code> to plot all parameters.

which

set to <code>TRUE</code> to use <code>rstan::traceplot</code> on a (presumed) stored <code>rstan</code> object in <code>x</code>, otherwise only real iterations are plotted and parameter values are shown as points instead of lines, with chains separated

rstan

plotno

set to <code>TRUE</code> to reverse direction for faceting chains

specifies size of chain facet label text, default is 8

stripsize

passed to <code>rstan::traceplot</code>

Regression modeling, testing, estimation, validation,
graphics, prediction, and typesetting by storing enhanced model design
attributes in the fit.  'rms' is a collection of functions that
assist with and streamline modeling.  It also contains functions for
binary and ordinal logistic regression models, ordinal models for
continuous Y with a variety of distribution families, and the Buckley-James
multiple regression model for right-censored responses, and implements
penalized maximum likelihood estimation for logistic and ordinary
linear models.  'rms' works with almost any regression model, but it
was especially written to work with binary or ordinal regression
models, Cox regression, accelerated failure time models,
ordinary linear models,	the Buckley-James model, generalized least
squares for serially or spatially correlated observations, generalized
linear models, and quantile regression.  Bayesian methods are implemented for binary and ordinal logistic regression with or without random effects.

stanDxplot: stanDxplot

Description

Usage

Arguments

Value

Details