predict method for gpss objects — predict.gpss • gpss

predict method for gpss objects

Usage

# S3 method for class 'gpss'
predict(
  object,
  newdata = NULL,
  type = "response",
  format = "default",
  interval = "confidence",
  level = 0.95,
  prior_mean = NULL,
  ...
)

Arguments

object: a model object for which prediction is desired.
newdata: data frame on which to make predictions (test set)
type: "response" or "scaled"
format: "default" or "rvar"
interval: "prediction" or "confidence"
level: a numerical value between 0 and 1
prior_mean: a numeric vector of prior mean values for Y at each test observation. Required when the model was trained with a prior_mean; see gp_predict. (default = NULL)
...: additional arguments (not used)

Examples

# \donttest{
library(gpss)
data(lalonde)
# categorical variables must be encoded as factors
dat <- transform(lalonde, race_ethnicity = factor(race_ethnicity))
# train and test sets
idx <- sample(seq_len(nrow(dat)), 500)
dat_train <- dat[idx, ]
dat_test <- dat[-idx, ]
# Fit model
mod <- gpss(re78 ~ nsw + age + educ + race_ethnicity, data = dat_train)
p <- predict(mod, newdata = dat_test)
p_confidence99 <- predict(mod, newdata = dat_test, interval = "confidence", level = 0.99)
# }