dmvnorm

logdmvnorm

Either a \(d\) - vector or an \(n\times d\) matrix, where \(d\)
 is the dimension of the normal distribution and \(n\) is the number of
 points at which the density is to be evaluated.

\(d\) - vector: Mean of the normal distribution (or NULL uses
 the origin as default)

This \(d\times d\) matrix is the variance matrix of the normal
 distribution (or NULL uses the identity matrix as default)

sigma

Density and log-density for the multivariate normal distribution 
 with mean equal to <code>mu</code>
 and variance matrix equal to <code>sigma</code>.

distribution

Analyzes finite mixture models for various parametric and semiparametric settings.  This includes mixtures of parametric distributions (normal, multivariate normal, multinomial, gamma), various Reliability Mixture Models (RMMs), mixtures-of-regressions settings (linear regression, logistic regression, Poisson regression, linear regression with changepoints, predictor-dependent mixing proportions, random effects regressions, hierarchical mixtures-of-experts), and tools for selecting the number of components (bootstrapping the likelihood ratio test statistic, mixturegrams, and model selection criteria).  Bayesian estimation of mixtures-of-linear-regressions models is available as well as a novel data depth method for obtaining credible bands.  This package is based upon work supported by the National Science Foundation under Grant No. SES-0518772.

Derek S. Young

mixtools

Tools for Analyzing Finite Mixture Models

Derek Young

Tatiana Benaglia

Didier Chauveau

David Hunter

Ryan Elmore

Thomas Hettmansperger

Hoben Thomas

Fengjuan Xuan

dmvnorm function

<dl> <dt>y</dt>
<dd>Either a \(d\) - vector or an \(n\times d\) matrix, where \(d\)
 is the dimension of the normal distribution and \(n\) is the number of
 points at which the density is to be evaluated.</dd> <dt>mu</dt>
<dd>\(d\) - vector: Mean of the normal distribution (or NULL uses
 the origin as default)</dd> <dt>sigma</dt>
<dd>This \(d\times d\) matrix is the variance matrix of the normal
 distribution (or NULL uses the identity matrix as default)</dd></dl>

Arguments

The Multivariate Normal Density — dmvnorm

<dl>

 <dt>y</dt>
<dd>Either a \(d\) - vector or an \(n\times d\) matrix, where \(d\)
 is the dimension of the normal distribution and \(n\) is the number of
 points at which the density is to be evaluated.</dd>

 <dt>mu</dt>
<dd>\(d\) - vector: Mean of the normal distribution (or NULL uses
 the origin as default)</dd>

 <dt>sigma</dt>
<dd>This \(d\times d\) matrix is the variance matrix of the normal
 distribution (or NULL uses the identity matrix as default)</dd>

</dl>

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dmvnorm: The Multivariate Normal Density

Description

Usage

Value

Arguments

Details

See Also