manylm.fit {mvabund}R Documentation

workhose functions for fitting multivariate linear models

Description

These are the workhorse functions called by manylm used to fit multivariate linear models. These should usually not be used directly unless by experienced users.

Usage

manylm.fit(x, y, offset = NULL, tol=1.0e-010, singular.ok = TRUE, ...)
manylm.wfit(x, y, w, offset = NULL, tol=1.0e-010, singular.ok = TRUE, ...)

Arguments

x design matrix of dimension n * p.
y matrix or an mvabund object of observations of dimension n*q.
w vector of weights (length n) to be used in the fitting process for the manylm.wfit functions. Weighted least squares is used with weights w, i.e., sum(w * e^2) is minimized.
offset numeric of length n). This can be used to specify an a priori known component to be included in the linear predictor during fitting.
tol tolerance for the qr decomposition. Default is 1.0e-050.
singular.ok logical. If FALSE, a singular model is an error.
... currently disregarded.

Value

a list with components

coefficients p vector
residuals n vector or matrix
fitted.values n vector or matrix
weights n vector — only for the *wfit* functions.
rank integer, giving the rank
qr (not null fits) the QR decomposition.
df.residual degrees of freedom of residuals
hat.X the hat matrix.
txX the matrix (t(x)%*%x).

Author(s)

Ulrike Naumann and David Warton <David.Warton@unsw.edu.au>.

See Also

manylm


[Package mvabund version 0.1-7 Index]