HOIF Estimators for Average Treatment Effect — transform

This file implements the Higher Order Influence Function (HOIF) estimators for Average Treatment Effect (ATE) estimation with nuisance functions.

Usage

transform_covariates(X, method = "splines", basis_dim, degree = 3, period = 1)

Arguments

X: Matrix of covariates (n x p)
method: Character: "splines", "fourier", or "none"
basis_dim: Integer: dimension of basis expansion per covariate (ignored if method = "none"; must be at least degree + 1 for "splines" and at least 2 for "fourier")
degree: Integer: degree for B-splines (default 3; ignored if method != "splines")
period: Numeric: period for Fourier basis (default 1; ignored if method != "fourier")

Value

Matrix of transformed covariates. For method = "none" the input X is returned unchanged (n x p); for "splines" and "fourier" the basis expansions of all covariates are column-bound together with an intercept column.

Author

Xingyu Chen Transform covariates to basis functions

Examples

X <- matrix(rnorm(40), nrow = 20, ncol = 2)
Z_splines <- transform_covariates(X, method = "splines", basis_dim = 5)
Z_fourier <- transform_covariates(X, method = "fourier", basis_dim = 4)
Z_raw <- transform_covariates(X, method = "none")
dim(Z_splines)
#> [1] 20  9
dim(Z_fourier)
#> [1] 20  9