R: Orderplot of iBMA objects

orderplot {BMA} | R Documentation

## Orderplot of iBMA objects

### Description

This function displays a plot showing the selection and rejection of variables being considered in an iterated Bayesian model averaging variable selection procedure.

### Usage

    orderplot(x, ...)

### Arguments

`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

### Details

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.

### Author(s)

Ian Painter ian.painter@AT@gmail.com

### See Also

`summary.iBMA.glm`, `iBMA`

### Examples

    ## Not run:
    ############ 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)

    ## End(Not run)

[Package BMA version 3.18.9 Index]