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Compute Sliced Inverse Regression

Source: R/sdr_kernels.R
compute_sir.Rd

Compute Sliced Inverse Regression

Usage

compute_sir(
  X,
  y,
  Sigma = NULL,
  nslices = 6,
  slice_type = c("quantile", "equal_width"),
  eps = 1e-08
)

Arguments

X

Numeric predictor matrix.

y

Numeric response vector.

Sigma

Covariance matrix used for standardisation.

nslices

Number of response slices.

slice_type

Slicing strategy.

eps

Eigenvalue floor.

Value

A list containing SIR kernel, eigenvalues, directions, scores, and slices.

Examples

X <- as.matrix(mtcars[, c("disp", "hp", "wt")])
fit <- compute_sir(X, y = mtcars$mpg, nslices = 4)
head(fit$eigenvalues)
#> [1] 0.81199072 0.06994048 0.01104979