plot.importance {LaplacesDemon}  R Documentation 
Plot Variable Importance
Description
This may be used to plot variable importance with BPIC, predictive
concordance, a discrepancy statistic, or the Lcriterion regarding an
object of class importance
.
Usage
## S3 method for class 'importance'
plot(x, Style="BPIC", ...)
Arguments
x 
This required argument is an object of class

Style 
When 
... 
Additional arguments are unused. 
Details
The xaxis is either BPIC (Ando, 2007), predictive concordance
(Gelfand, 1996), a discrepancy statistic (Gelman et al., 1996), or the
Lcriterion (Laud and Ibrahim, 1995) of the Importance
function (depending on the Style
argument), and variables are
on the yaxis. A more important variable is associated with a dot that
is plotted farther to the right. For more information on variable
importance, see the Importance
function.
Author(s)
Statisticat, LLC software@bayesianinference.com
References
Ando, T. (2007). "Bayesian Predictive Information Criterion for the Evaluation of Hierarchical Bayesian and Empirical Bayes Models". Biometrika, 94(2), p. 443–458.
Gelfand, A. (1996). "Model Determination Using Sampling Based Methods". In Gilks, W., Richardson, S., Spiegehalter, D., Chapter 9 in Markov Chain Monte Carlo in Practice. Chapman and Hall: Boca Raton, FL.
Gelman, A., Meng, X.L., and Stern H. (1996). "Posterior Predictive Assessment of Model Fitness via Realized Discrepancies". Statistica Sinica, 6, p. 733–807.
Laud, P.W. and Ibrahim, J.G. (1995). "Predictive Model Selection". Journal of the Royal Statistical Society, B 57, p. 247–262.