<code>concoef</code> is a generic function which extracts the constrained
 (canonical) coefficients from objects returned by certain modelling
 functions.

concoef

An implementation of about 6 major classes of
statistical regression models. The central algorithm is
Fisher scoring and iterative reweighted least squares.
At the heart of this package are the vector generalized linear
and additive model (VGLM/VGAM) classes. VGLMs can be loosely
thought of as multivariate GLMs. VGAMs are data-driven
VGLMs that use smoothing. The book "Vector Generalized
Linear and Additive Models: With an Implementation in R"
(Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of
the statistical framework and the package. Currently only
fixed-effects models are implemented. Many (100+) models and
distributions are estimated by maximum likelihood estimation
(MLE) or penalized MLE. The other classes are RR-VGLMs
(reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained
RR-VGLMs, quadratic RR-VGLMs, reduced-rank VGAMs,
RCIMs (row-column interaction models)---these classes perform
constrained and unconstrained quadratic ordination (CQO/UQO)
models in ecology, as well as constrained additive ordination
(CAO). Hauck-Donner effect detection is implemented.
Note that these functions are subject to change;
see the NEWS and ChangeLog files for latest changes.

Thomas Yee

VGAM

Vector Generalized Linear and Additive Models

Cleve Moler

concoef function

Extract Model Constrained/Canonical Coefficients — concoef

<dl>

 <dt>object</dt>
<dd>An object for which the extraction of canonical
 coefficients is meaningful.
</dd>

 <dt>...</dt>
<dd>Other arguments fed into the specific
 methods function of the model.
</dd>

</dl>

Arguments

Author

<code>concoef</code> replaces <code>ccoef</code>;
 the latter is deprecated.





For QO models, there is a direct inverse relationship between the
 scaling of the latent variables (site scores) and the tolerances.
 One normalization is for the latent variables to have unit variance.
 Another normalization is for all the species' tolerances to be
 unit (provided <code>eq.tolerances</code> is <code>TRUE</code>). These two
 normalizations cannot simultaneously hold in general. For rank
 \(R\) models with \(R&gt;1\) it becomes more complicated because
 the latent variables are also uncorrelated. An important argument when
 fitting quadratic ordination models is whether <code>eq.tolerances</code>
 is <code>TRUE</code> or <code>FALSE</code>. See Yee (2004) for details.

concoef: Extract Model Constrained/Canonical Coefficients

Description

Usage

Arguments

Value

Details

References

See Also

Examples