airAccs

datasets

Functions and data are provided that support a course
that emphasizes statistical issues of inference and generalizability.
The functions are designed to make it straightforward to illustrate
the use of cross-validation, the training/test approach, simulation,
and model-based estimates of accuracy.  Methods considered are
Generalized Additive Modeling, Linear and Quadratic Discriminant
Analysis, Tree-based methods, and Random Forests.

John Maindonald

gamclass

Functions and Data for a Course on Modern Regression and
Classification

airAccs function

A data frame with 5666 observations on the following 7 variables.<dl>
 <dt><code>Date</code></dt>
<dd>Date of Accident</dd> <dt><code>location</code></dt>
<dd>Location of accident</dd> <dt><code>operator</code></dt>
<dd>Aircraft operator</dd> <dt><code>planeType</code></dt>
<dd>Aircraft type</dd> <dt><code>Dead</code></dt>
<dd>Number of deaths</dd> <dt><code>Aboard</code></dt>
<dd>Number aboard</dd> <dt><code>Ground</code></dt>
<dd>Deaths on ground</dd>
 
 
</dl>

Format

Aircraft Crash data — airAccs

A data frame with 5666 observations on the following 7 variables.<dl>
 <dt><code>Date</code></dt>
<dd>Date of Accident</dd>

 <dt><code>location</code></dt>
<dd>Location of accident</dd>

 <dt><code>operator</code></dt>
<dd>Aircraft operator</dd>

 <dt><code>planeType</code></dt>
<dd>Aircraft type</dd>

 <dt><code>Dead</code></dt>
<dd>Number of deaths</dd>

 <dt><code>Aboard</code></dt>
<dd>Number aboard</dd>

 <dt><code>Ground</code></dt>
<dd>Deaths on ground</dd>
 
 
</dl>

airAccs: Aircraft Crash data

Description

Usage

Arguments

Format

Details

References

Examples