blauduncan


Sample of 20,700 subjects for which 5 variables are measured:
  <table><tr><td>
    $V$ </td>
<td> : </td>
</tr><tr><td>   Father's educational attainment,</td>
<td> 
    $X$ </td>
</tr><tr><td> : </td>
<td>   Father's occupational status,</td>
</tr><tr><td> 
    $U$ </td>
<td> : </td>
</tr><tr><td>   educational attainment,</td>
<td> 
    $W$ </td>
</tr><tr><td> : </td>
<td>   Status of first-job,</td>
</tr></table>


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

blauduncan function

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

Format

Blau, P. \& Duncan, O. (1967) <em>The American Occupational
    Structure</em>. New York: Wiley. (See p.13 and p.169).

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

blauduncan: Blau and Duncan's data on the American occupational structure

Description

Usage

Arguments

Format

Source

References

Examples

$V$	:
Father's educational attainment,	$X$
:	Father's occupational status,
$U$	:
educational attainment,	$W$
:	Status of first-job,