mathmarks


Examination marks of 88 students in the five subjects:
  <ul>
<li> Mechanics,
    </li>
<li> Vectors,
    </li>
<li> Algebra,
    </li>
<li> Analysis,
    </li>
<li> Statistics.
  </li>
</ul><p></p><p></p>

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

mathmarks function

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

Format

Mardia, K.V., Kent, J.T. \& Bibby, J.M. (1979) <em>Multivariate
    analysis</em>. London: Academic Press. (See pp.3-4). Whittaker, J. (1990) <em>Graphical models in applied
    multivariate statistics</em>. Chichester: Wiley. (See Ch. 1.1).

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

mathmarks: Mathematics marks

Description

Usage

Arguments

Format

Source

Details

Examples