predict.fosr: Prediction from a fitted bayes_fosr model

In refunders/refund: Regression with Functional Data

Prediction from a fitted bayes_fosr model

Description

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.

Usage

## S3 method for class 'fosr'
predict(object, newdata, ...)

Arguments

object	a fitted fosr object as produced by bayes_fosr
newdata	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

Value

...

Author(s)

Jeff Goldsmith [e-mail]

See Also

bayes_fosr

Examples

## 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))

## End(Not run)

refunders/refund documentation built on March 20, 2024, 7:11 a.m.