moth

The data are of sample size 72 and contain 6 variables:
 <dl>
 <dt>min</dt><dd>minimum night temperature</dd>
,
 <dt>max</dt><dd>previous day's maximum temperature</dd>
,
 <dt>wind</dt><dd>average wind speed during night</dd>
,
 <dt>rain</dt><dd>amount of rain during night</dd>
,
 <dt>cloud</dt><dd>percentage of starlight obscured by clouds</dd>
,
 <dt>moth</dt><dd>number of moths caught in a light trap in one 
night</dd>
.
 </dl>

datasets

This package provides routines to perform SIN model selection
as described in Drton & Perlman (2004, 2008).  The selected models are
represented in the format of the 'ggm' package, which allows in
particular parameter estimation in the selected model.

Mathias Drton

A SINful Approach to Selection of Gaussian Graphical Markov
Models

moth function

A list providing a summary of the data. The list contains:
 <table><tr><td>
 <code>moth$means</code> </td>
<td> : </td>
</tr><tr><td> the mean vector,</td>
<td> 
 <code>moth$stddev</code> </td>
</tr><tr><td> : </td>
<td> the vector of standard deviations,</td>
</tr><tr><td>
 <code>moth$corr</code> </td>
<td> : </td>
</tr><tr><td> the correlation matrix, and </td>
<td>
 <code>moth$means</code> </td>
</tr></table>

Format

Whittaker, J. (1990) Graphical models in applied
 multivariate statistics. Chichester: Wiley. (See Ch. 10.3).

`moth$means`	:
the mean vector,	`moth$stddev`
:	the vector of standard deviations,
`moth$corr`	:
the correlation matrix, and	`moth$means`

moth: Noctuid Moth Trappings

Description

Usage

Arguments

Format

Source

Examples