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This function displays a plot showing the selection and rejection of variables being considered in an iterated Bayesian model averaging variable selection procedure.
orderplot(x, ...)
an object of type iBMA.glm, iBMA.bicreg, iBMA.surv, iBMA.intermediate.glm, iBMA.intermediate.bicreg or iBMA.intermediate.surv.
other parameters to be passed to plot.default
Ian Painter ian.painter@gmail.com
The x-axis represents iterations, the y-axis variables. For each variable, a dot in the far left indicates that the variable has not yet been examined, a black line indicates the variable has been examined and dropped, the start of the line represents when the variable was first examined, the end represents when the variable was dropped. A blue line represents a variable that is still in the selected set of variables. If the iterations have completed then the blue lines end with blue dots, representing the final set of variables selected.
summary.iBMA.glm
, iBMA
if (FALSE) {
############ iBMA.glm
library("MASS")
data(birthwt)
y<- birthwt$lo
x<- data.frame(birthwt[,-1])
x$race<- as.factor(x$race)
x$ht<- (x$ht>=1)+0
x<- x[,-9]
x$smoke <- as.factor(x$smoke)
x$ptl<- as.factor(x$ptl)
x$ht <- as.factor(x$ht)
x$ui <- as.factor(x$ui)
### add 41 columns of noise
noise<- matrix(rnorm(41*nrow(x)), ncol=41)
colnames(noise)<- paste('noise', 1:41, sep='')
x<- cbind(x, noise)
iBMA.glm.out<- iBMA.glm(x, y, glm.family="binomial", factor.type=FALSE,
verbose = TRUE, thresProbne0 = 5 )
orderplot(iBMA.glm.out)
}
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