This may be used to plot variable importance with BPIC, predictive
concordance, a discrepancy statistic, or the L-criterion regarding an
object of class importance.
# S3 method for importance
plot(x, Style="BPIC", …)This required argument is an object of class
importance.
When Style="BPIC", BPIC is shown, and BPIC
is the default. Otherwise, predictive concordance is plotted when
Style="Concordance", a discrepancy statistic is plotted when
Style="Discrep", or the L-criterion is plotted when
Style="L-criterion".
Additional arguments are unused.
The x-axis is either BPIC (Ando, 2007), predictive concordance
(Gelfand, 1996), a discrepancy statistic (Gelman et al., 1996), or the
L-criterion (Laud and Ibrahim, 1995) of the Importance
function (depending on the Style argument), and variables are
on the y-axis. 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.
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.