plotComp {BMS} | R Documentation |
Plots a comparison of posterior inclusion probabilites, coefficients or their standard deviation between various bma objects
plotComp(..., varNr = NULL, comp = "PIP", exact = FALSE, include.legend = TRUE, add.grid = TRUE, do.par = TRUE, cex.xaxis = 0.8)
... |
one or more objects of class 'bma' to be compared. |
varNr |
optionally, covariate indices to be included in the plot, can be either integer vector or character vector - see examples |
comp |
a character denoting what should be compared: |
exact |
if |
include.legend |
whether to include a default legend in the plot (custom legends can be added with the command |
add.grid |
whether to add a |
do.par |
whether to adjust |
cex.xaxis |
font size scaling parameter for the x-axis - cf. argument |
Martin Feldkircher and Stefan Zeugner
coef.bma
for the underlying function
Check http://bms.zeugner.eu for additional help.
## sample two simple bma objects data(datafls) mm1=bms(datafls[,1:15]) mm2=bms(datafls[,1:15]) #compare PIPs plotComp(mm1,mm2) #compare standardized coefficeitns plotComp(mm1,mm2,comp="Std Mean") #...based on the lieklihoods of best models plotComp(mm1,mm2,comp="Std Mean",exact=TRUE) #plot only PIPs for first four covariates plotComp(mm1,mm2,varNr=1:4, col=c("black","red")) #plot only coefficients for covariates 'GDP60 ' and 'LifeExp' plotComp(mm1,mm2,varNr=c("GDP60", "LifeExp"),comp="Post Mean")