manylm.fit

manylm.wfit

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

multivariate

regression

array

A set of tools for displaying, modeling and analysing
multivariate abundance data in community ecology. See
'mvabund-package.Rd' for details of overall package organization.
The package is implemented with the Gnu Scientific Library
(<http://www.gnu.org/software/gsl/>) and 'Rcpp'
(<http://dirk.eddelbuettel.com/code/rcpp.html>) 'R' / 'C++' classes.

David Warton

mvabund

Statistical Methods for Analysing Multivariate Abundance Data

Yi Wang

Ulrike Naumann

Dirk Eddelbuettel

John Wilshire

Julian Byrnes

Ralph dos Santos Silva

Jenni Niku

Ian Renner

Stephen Wright

manylm.fit function

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

Arguments

Ulrike Naumann and David Warton &lt;David.Warton@unsw.edu.au&gt;.

Author

workhose functions for fitting multivariate linear models — manylm.fit

<dl>

 <dt>x</dt>
<dd>design matrix of dimension <code>n * p</code>.</dd>

 <dt>y</dt>
<dd>matrix or an <code>mvabund</code> object of observations of dimension <code>n*q</code>.</dd>

 <dt>w</dt>
<dd>vector of weights (length <code>n</code>) to be used in the fitting
 process for the <code>manylm.wfit</code> functions. Weighted least squares is
 used with weights <code>w</code>, i.e., <code>sum(w * e^2)</code> is minimized.</dd>

 <dt>offset</dt>
<dd>numeric of length <code>n</code>). This can be used to
 specify an a priori known component to be included in the
 linear predictor during fitting.</dd>

 <dt>tol</dt>
<dd>tolerance for the <code>qr</code> decomposition. Default
 is 1.0e-050.</dd>

 <dt>singular.ok</dt>
<dd>logical. If <code>FALSE</code>, a singular model is an
 error.</dd>

 <dt>...</dt>
<dd>currently disregarded.</dd>

</dl>

workhose functions for fitting multivariate linear models

manylm.fit: workhose functions for fitting multivariate linear models

Description

Usage

Value

Arguments

Author

See Also