rrvglm.optim.control

Passed into <code>optim</code> as <code>fnscale</code>.

Fnscale

Passed into <code>optim</code> as <code>maxit</code>.

Maxit

Iteration number when the "Nelder-Mead" method
 of <code>optim</code> is switched to the quasi-Newton "BFGS" method.
 Assigning <code>Switch.optimizer</code> a negative number
 means always BFGS, while assigning <code>Switch.optimizer</code> a value
 greater than <code>maxits</code> means always use Nelder-Mead.

Switch.optimizer

Passed into <code>optim</code> as <code>abstol</code>.

Abstol

Passed into <code>optim</code> as <code>reltol</code>.

Reltol

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Algorithmic constants and parameters for running <code>optim</code> within
 <code>rrvglm</code> are set using this function.

models

regression

An implementation of about 6 major classes of
statistical regression models. At the heart of it are the
vector generalized linear and additive model (VGLM/VGAM)
classes, and 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 VGAM package.
Currently only fixed-effects models are implemented,
i.e., no random-effects models. Many (150+) models and
distributions are estimated by maximum likelihood estimation
(MLE) or penalized MLE, using Fisher scoring. VGLMs can be
loosely thought of as multivariate GLMs. VGAMs are data-driven
VGLMs (i.e., with smoothing). The other classes are RR-VGLMs
(reduced-rank 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). Note that these functions are subject to change;
see the NEWS and ChangeLog files for latest changes.

rrvglm.optim.control: Control Function for rrvglm() Calling optim()

Description

Usage

Arguments

Value

Details

See Also