
Data on 102 male and 100 female athletes collected at the Australian
Institute of Sport.


datasets

Functions, methods, and datasets for fitting dimension
reduction regression, using slicing (methods SAVE and SIR), Principal
Hessian Directions (phd, using residuals and the response), and an
iterative IRE.  Partial methods, that condition on categorical
predictors are also available.  A variety of tests, and stepwise
deletion of predictors, is also included.  Also included is
code for computing permutation tests of dimension.  Adding additional
methods of estimating dimension is straightforward.
For documentation, see the vignette in the package.   With version 3.0.4,
the arguments for dr.step have been modified.

Sanford Weisberg

Methods for Dimension Reduction for Regression

ais function

This data frame contains the following columns:
 <dl>
    <dt>Sex</dt><dd>
 (0 = male or 1 = female)
    </dd> <dt>Ht</dt><dd>
 height (cm)
    </dd> <dt>Wt</dt><dd>
 weight (kg)
    </dd> <dt>LBM</dt><dd>
 lean body mass
    </dd> <dt>RCC</dt><dd>
 red cell count
    </dd> <dt>WCC</dt><dd>
 white cell count
    </dd> <dt>Hc</dt><dd>
 Hematocrit
    </dd> <dt>Hg</dt><dd>
 Hemoglobin
    </dd> <dt>Ferr</dt><dd>
 plasma ferritin concentration
    </dd> <dt>BMI</dt><dd>
 body mass index, weight/(height)**2
    </dd> <dt>SSF</dt><dd>
 sum of skin folds
    </dd> <dt>Bfat</dt><dd>
 Percent body fat
    </dd> <dt>Label</dt><dd>
 Case Labels
    </dd> <dt>Sport</dt><dd>
 Sport
    </dd> </dl> 

ais: Australian institute of sport data

Description

Arguments

Format

Source

References

Examples