glucose


From an investigation of determinants of blood glucose control.  Data on
39 diabetic patients.  The 4 variables are:
  <ul>
<li> glycosylated hemoglobin GHb,
    </li>
<li> knowledge about the illness,
    </li>
<li> duration of the illness,
    </li>
<li> fatalism (measure of patient's attitude to disease).
  </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

glucose function

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

Format

Cox, D.R. \& Wermuth, N.  (1993)  Linear Dependencies Represented by
  Chain Graphs.  <em>Statistical Science</em> 8(3): 204-283. (See Table 7).

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

glucose: Glucose

Description

Usage

Arguments

Format

Source

Examples