put.smart

a list containing parameters needed later for smart prediction.

smart

Adds a list to the end of the list <code>.smart.prediction</code>
in
<code>smartpredenv</code>.

models

regression

programming

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.

Thomas Yee

VGAM

Vector Generalized Linear and Additive Models

put.smart function

The variable <code>.smart.prediction.counter</code> in
 <code>smartpredenv</code>
 is incremented beforehand,
 and <code>.smart.prediction[[.smart.prediction.counter]]</code> is
 assigned the list <code>smart</code>. 
 If the list <code>.smart.prediction</code> in
 <code>smartpredenv</code>
 is not long enough
 to hold <code>smart</code>, then it is made larger, and the variable
 <code>.max.smart</code> in
 <code>smartpredenv</code>
 is adjusted accordingly.

put.smart: Adds a List to the End of the List ``.smart.prediction''

Description

Usage

Arguments

Value

Side Effects

Details

See Also

Examples