gratia (version 0.9.0)

lp_matrix: Return the linear prediction matrix of a fitted GAM

Description

lp_matrix() is a wrapper to predict(..., type = "lpmatrix") for returning the linear predictor matrix for the model training data (when data = NULL), or user-specified data values supplied via data.

Usage

lp_matrix(model, ...)
# S3 method for gam
lp_matrix(model, data = NULL, ...)

Value

The linear prediction matrix is returned as a matrix. The object returned is of class "lp_matrix", which inherits from classes "matrix"

and "array". The special class allows the printing of the matrix to be controlled, which we do by printing the matrix as a tibble.

Arguments

model

a fitted model

...

arguments passed to other methods and predict methods including mgcv::predict.gam() and mgcv::predict.bam()

data

a data frame of values at which to return the linear prediction matrix.

Details

The linear prediction matrix \(\mathbf{X}_p\) is a matrix that maps values of parameters \(\hat{\mathbf{\beta}}_p\) to values on the linear predictor of the model \(\hat{\eta}_p = \mathbf{X}_p \hat{\mathbf{\beta}}_p\). \(\mathbf{X}_p\) is the model matrix where spline covariates have been replaced by the values of the basis functions evaluated at the respective covariates. Parametric covariates are also included.

Examples

load_mgcv()
# \dontshow{
op <- options(pillar.sigfig = 3, cli.unicode = FALSE)
# }
df <- data_sim("eg1", seed = 1)
m <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = df)

# linear prediction matrix for observed data
xp <- lp_matrix(m)
## IGNORE_RDIFF_BEGIN
xp
## IGNORE_RDIFF_END

# the object `xp` *is* a matrix
class(xp)
# but we print like a tibble to avoid spamming the R console

# linear predictor matrix for new data set
ds <- data_slice(m, x2 = evenly(x2))
xp <- lp_matrix(m, data = ds)
## IGNORE_RDIFF_BEGIN
xp
## IGNORE_RDIFF_END
# \dontshow{
options(op)
# }