Predict Method for fitted MID Models

The method of predict() for "mid" objects obtains predictions from a fitted MID model.

Usage

# S3 method for class 'mid'
predict(
  object,
  newdata = NULL,
  na.action = "na.pass",
  type = c("response", "link", "terms"),
  terms = object$terms,
  ...
)

mid.f(object, term, x, y = NULL)

Arguments

object: a "mid" object to be used to make predictions.
newdata: a data frame of the new observations.
na.action: a function or character string specifying what should happen when the data contain NAs.
type: the type of prediction required. The default is on the scale of the response varialbe. The alternative "link" is on the scale of the linear predictors. The "terms" option returns a matrix giving the fitted values of each term in the model formula on the linear predictor scale.
terms: a character vector of term labels, specifying a subset of component functions to be used to make predictions.
...: not used.
term: a character string specifying the component function of a fitted MID model.
x: a matrix, data frame or vector to be used as the input to the first argument of the component function. If a matrix or data frame is passed, inputs for both x and y are extracted from it.
y: a vector to be used as the input to the second argument of the component function.

Value

predict.mid() returns a numeric vector of MID model predictions.

Details

The S3 method of predict() for MID models returns the model predictions. mid.f() works as a component function of a MID model.

Examples

data(trees, package = "datasets")
idx <- c(5L, 10L, 15L, 20L, 25L, 30L)
mid <- interpret(Volume ~ .^2, trees[-idx,], lambda = 1)
#> 'model' not passed: response variable in 'data' is used
trees[idx, "Volume"]
#> [1] 18.8 19.9 19.1 24.9 42.6 51.0
predict(mid, trees[idx,])
#> [1] 18.55337 20.58210 22.14285 23.46519 45.01464 57.83952
predict(mid, trees[idx,], type = "terms")
#>           Girth     Height Girth:Height
#> [1,] -12.738856  1.1216360 -0.189405623
#> [2,]  -8.033129 -1.7644569  0.019681599
#> [3,]  -6.497487 -1.7644569  0.044798668
#> [4,]  -1.870473 -4.7782653 -0.246067966
#> [5,]  15.096778 -0.4426815  0.000545126
#> [6,]  27.372413  0.1252837 -0.018178806
#> attr(,"constant")
#> [1] 30.36
mid.f(mid, "Girth", trees[idx,])
#> [1] -12.738856  -8.033129  -6.497487  -1.870473  15.096778  27.372413
mid.f(mid, "Girth:Height", trees[idx,])
#> [1] -0.189405623  0.019681599  0.044798668 -0.246067966  0.000545126
#> [6] -0.018178806
predict(mid, trees[idx,], terms = c("Girth", "Height"))
#> [1] 18.74278 20.56241 22.09806 23.71126 45.01410 57.85770