wgcm: Weighted Generalised covariance measure test

In comets: Covariance Measure Tests for Conditional Independence

Weighted Generalised covariance measure test

Description

Weighted Generalised covariance measure test

Usage

wgcm(
  Y,
  X,
  Z,
  reg_YonZ = "rf",
  reg_XonZ = "rf",
  reg_wfun = "rf",
  args_YonZ = NULL,
  args_XonZ = NULL,
  args_wfun = NULL,
  frac = 0.5,
  B = 499L,
  coin = TRUE,
  cointrol = NULL,
  return_fitted_models = FALSE,
  multivariate = c("none", "YonZ", "XonZ", "both"),
  ...
)

Arguments

Y	Vector of response values. Can be supplied as a numeric vector or a single column matrix.
X	Matrix or data.frame of covariates.
Z	Matrix or data.frame of covariates.
reg_YonZ	Character string or function specifying the regression for Y on Z. See ?regressions for more detail.
reg_XonZ	Character string or function specifying the regression for X on Z. See ?regressions for more detail.
reg_wfun	Character string or function specifying the regression for estimating the weighting function. See ?regressions for more detail.
args_YonZ	A list of named arguments passed to reg_YonZ.
args_XonZ	A list of named arguments passed to reg_XonZ.
args_wfun	Additional arguments passed to reg_XonZ.
frac	Relative size of train split.
B	Number of bootstrap samples. Only applies if type = "max" is used.
coin	Logical; whether or not to use the coin package for computing the test statistic and p-value. The coin package computes variances with n - 1 degrees of freedom. The default is TRUE.
cointrol	List; further arguments passed to independence_test.
return_fitted_models	Logical; whether to return the fitted regressions (default is FALSE).
multivariate	Character; specifying which regression can handle multivariate outcomes ("none", "YonZ", "XonZ", or "both"). If "none", then the regression is run using each column in Y (or X) as the response.
...	Additional arguments currently ignored.

Details

The weighted generalised covariance measure test tests whether a weighted version of the conditional covariance of Y and X given Z is zero.

Value

Object of class 'wgcm' and 'htest' with the following components:

statistic	The value of the test statistic.
p.value	The p-value for the hypothesis
parameter	In case X is multidimensional, this is the degrees of freedom used for the chi-squared test.
hypothesis	String specifying the null hypothesis .
null.value	String specifying the null hypothesis.
method	The string "Generalised covariance measure test".
data.name	A character string giving the name(s) of the data.
rY	Residuals for the Y on Z regression.
rX	Weighted residuals for the X on Z regression.
W	Estimated weights.
models	List of fitted regressions if return_fitted_models is TRUE.

References

Scheidegger, C., Hörrmann, J., & Bühlmann, P. (2022). The weighted generalised covariance measure. Journal of Machine Learning Research, 23(273), 1-68.

Examples

n <- 100
X <- matrix(rnorm(2 * n), ncol = 2)
colnames(X) <- c("X1", "X2")
Z <- matrix(rnorm(2 * n), ncol = 2)
colnames(Z) <- c("Z1", "Z2")
Y <- X[, 2]^2 + Z[, 2] + rnorm(n)
(wgcm1 <- wgcm(Y, X, Z))

comets documentation built on April 4, 2025, 1:24 a.m.