mvabund (version 3.1)

manylm.fit: 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).

See Also

manylm