Takes a fitted fosr-object produced by bayes_fosr and produces predictions given a
new set of values for the model covariates or the original values used for the model fit.
# S3 method for fosr
predict(object, newdata, ...)a fitted fosr object as produced by bayes_fosr
a named list containing the values of the model covariates at which predictions are required. If this is not provided then predictions corresponding to the original data are returned. All variables provided to newdata should be in the format supplied to the model fitting function.
additional (unused) arguments
...
# NOT RUN {
library(reshape2)
library(dplyr)
library(ggplot2)
##### Cross-sectional real-data example #####
## organize data
data(DTI)
DTI = subset(DTI, select = c(cca, case, pasat))
DTI = DTI[complete.cases(DTI),]
DTI$gender = factor(sample(c("male","female"), dim(DTI)[1], replace = TRUE))
DTI$status = factor(sample(c("RRMS", "SPMS", "PPMS"), dim(DTI)[1], replace = TRUE))
## fit models
VB = bayes_fosr(cca ~ pasat, data = DTI, Kp = 4, Kt = 10)
## obtain predictions
pred = predict(VB, sample_n(DTI, 10))
# }
# NOT RUN {
# }