mlmtst: Sums of Squares and Pseudo-F Statistics from a Multivariate...

In isglobal-brge/epimutacions: Robust outlier identification for DNA methylation data

Sums of Squares and Pseudo-F Statistics from a Multivariate Fit

Description

Computes the sum of squares, degrees of freedom, pseudo-F statistics and partial R-squared for each predictor from a multivariate fit. It also returns the eigenvalues of the residual covariance matrix.

Usage

mlmtst(fit, X, subset = NULL, tol = 0.001)

Arguments

fit	multivariate fit obtained by lm.
X	design matrix obtained by model.matrix.
subset	subset of predictors for which summary statistics will be reported. Note that this is different from the "subset" argument in lm.
tol	e[e/sum(e) > tol], where e is the vector of eigenvalues of the residual covariance matrix. Required to prevent long running times of algorithm AS 204. Default is 0.001 to ensure minimal loss of accuracy.

Details

Different types of sums of squares (i.e. "I", "II" and "III") are available.

Value

A list containing:

SS	sums of squares for all predictors (and residuals).
df	degrees of freedom for all predictors (and residuals).
f.tilde	pseudo-F statistics for all predictors.
r2	partial R-squared for all predictors.
e	eigenvalues of the residual covariance matrix.

Author(s)

Diego Garrido-Martín

See Also

AS204

isglobal-brge/epimutacions documentation built on April 22, 2024, 4:08 a.m.