This data set consists of 654 observations on children aged 3 to 19. Forced Expiratory Volume (FEV), which is a measure of lung capacity, is the variable in interest. Age and height are two continuous predictors. Sex and smoke are two categorical predictors.

data sets

Routines doing cone projection and quadratic programming, as well as doing estimation and inference for constrained parametric regression and shape-restricted regression problems. See Mary C. Meyer (2013)<doi:10.1080/03610918.2012.659820> for more details.

Xiyue Liao

coneproj

Primal or Dual Cone Projections with Routines for Constrained
Regression

FEV function

A data frame with 654 observations on the following 5 variables.<dl>
 <dt><code>age</code></dt>
<dd>Age of the 654 children.</dd> <dt><code>FEV</code></dt>
<dd>Forced expiratory volume(liters).</dd> <dt><code>height</code></dt>
<dd>Height(inches).</dd> <dt><code>sex</code></dt>
<dd>Female is 0. Male is 1.</dd> <dt><code>smoke</code></dt>
<dd>Nonsmoker is 0. Smoker is 1.</dd> 
</dl>

Format

Forced Expiratory Volume — FEV

A data frame with 654 observations on the following 5 variables.<dl>
 <dt><code>age</code></dt>
<dd>Age of the 654 children.</dd>

 <dt><code>FEV</code></dt>
<dd>Forced expiratory volume(liters).</dd>

 <dt><code>height</code></dt>
<dd>Height(inches).</dd>

 <dt><code>sex</code></dt>
<dd>Female is 0. Male is 1.</dd>

 <dt><code>smoke</code></dt>
<dd>Nonsmoker is 0. Smoker is 1.</dd>

 
</dl>

FEV: Forced Expiratory Volume

Description

Usage

Arguments

Format