Binormcop

dbinormcop

pbinormcop

rbinormcop

Density, distribution function,
 and random generation
 for the (one parameter) bivariate
 Gaussian copula distribution.

distribution

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

Binormcop function

<dl> <dt>x1, x2, q1, q2</dt>
<dd>vector of quantiles.
 The <code>x1</code> and <code>x2</code> should be in the interval
 \((0,1)\). Ditto for <code>q1</code> and <code>q2</code>.</dd> <dt>n</dt>
<dd>number of observations.
 Same as <code><a href="/link/rnorm?package=VGAM&version=1.1-11" data-mini-rdoc="VGAM::rnorm">rnorm</a></code>.
</dd> <dt>rho</dt>
<dd>the correlation parameter.
 Should be in the interval \((-1,1)\).</dd> <dt>log</dt>
<dd>Logical.
 If <code>TRUE</code> then the logarithm is returned.
</dd></dl>

Arguments

Author

Density, distribution function,
 and random generation
 for the (one parameter) bivariate
 Gaussian copula distribution.

Gaussian Copula (Bivariate) Distribution — Binormcop

<dl>

 <dt>x1, x2, q1, q2</dt>
<dd>vector of quantiles.
 The <code>x1</code> and <code>x2</code> should be in the interval
 \((0,1)\). Ditto for <code>q1</code> and <code>q2</code>.

</dd>

 <dt>n</dt>
<dd>number of observations.
 Same as <code><a href='https://rdrr.io/r/stats/Normal.html'>rnorm</a></code>.
</dd>

 <dt>rho</dt>
<dd>the correlation parameter.
 Should be in the interval \((-1,1)\).

</dd>

 <dt>log</dt>
<dd>Logical.
 If <code>TRUE</code> then the logarithm is returned.


</dd>

</dl>

Get 50% off unlimited learning

Binormcop: Gaussian Copula (Bivariate) Distribution

Description

Usage

Value

Arguments

Author

Details

See Also

Examples