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

&#8230;

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. 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 (150+) 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, 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