Predict outcomes from a fitted MaGP model

Returns predictions for new quantitative-sequence inputs. Plug-in standard errors and variances can be returned with the predictions.

Usage

# S3 method for class 'magp2d'
predict(
  object,
  newdata,
  se.fit = FALSE,
  type = c("script", "response", "latent"),
  ...
)

# S3 method for class 'magpfull'
predict(
  object,
  newdata,
  se.fit = FALSE,
  type = c("script", "response", "latent"),
  ...
)

Arguments

object

A fitted magp2d or magpfull object.

newdata

A numeric matrix or data frame with the same quantitative and sequence inputs used for fitting. A response column named y is ignored.

se.fit

Logical; if TRUE, return predictive standard errors and variances in addition to fitted values.

type

Prediction convention. "script" uses the fitted training-row convention when newdata exactly matches a training row. "response" includes the nugget variance for a future response, and "latent" returns uncertainty for the noise-free surface.

...

Additional arguments, currently unused.

Value

If se.fit = FALSE, a numeric vector of predictions. Otherwise, a list with components fit, se.fit, variance, and type.

Examples

# \donttest{
train <- read.table(
  system.file("extdata", "example_train.txt", package = "magp"),
  header = TRUE
)
test <- read.table(
  system.file("extdata", "example_test.txt", package = "magp"),
  header = TRUE
)
fit <- magp2d_fit(train, seed = 1)
predict(fit, test[1:3, ], se.fit = TRUE, type = "response")
#> $fit
#> [1] 17.13052 29.49620 13.28978
#> 
#> $se.fit
#> [1] 30.50386 32.70545 34.35567
#> 
#> $variance
#> [1]  930.4855 1069.6463 1180.3119
#> 
#> $type
#> [1] "response"
#> 
# }