plasma

This data set is used for the routine plotpersp. It contains 314 observations of blood plasma, beta carotene measurements along with several covariates. High levels of blood plasma and beta carotene are believed to be protective against cancer, and it is of interest to determine the relationships with covariates.

datasets

A constrained generalized additive model is fitted by the cgam routine. Given a set of predictors, each of which may have a shape or order restrictions, the maximum likelihood estimator for the constrained generalized additive model is found using an iteratively re-weighted cone projection algorithm. The ShapeSelect routine chooses a subset of predictor variables and describes the component relationships with the response. For each predictor, the user needs only specify a set of possible shape or order restrictions. A model selection method chooses the shapes and orderings of the relationships as well as the variables. The cone information criterion (CIC) is used to select the best combination of variables and shapes. A genetic algorithm may be used when the set of possible models is large. In addition, the cgam routine implements a two-dimensional isotonic regression using warped-plane splines without additivity assumptions. It can also fit a convex or concave regression surface with triangle splines without additivity assumptions. See Liao X, Meyer MC (2019)<doi:10.18637/jss.v089.i05> for more details.

Xiyue Liao

cgam

Constrained Generalized Additive Model

Mary Meyer

plasma function

<dl>
 <dt><code>logplasma</code></dt>
<dd>A numeric vector of the logarithm of plasma levels.</dd> <dt><code>betacaro</code></dt>
<dd>A numeric vector of dietary beta carotene consumed mcg per day.</dd> <dt><code>bmi</code></dt>
<dd>A numeric vector of BMI values.</dd> <dt><code>cholest</code></dt>
<dd>A numeric vector of cholesterol consumed mg per day.</dd> <dt><code>dietfat</code></dt>
<dd>A numeric vector of the logarithm of grams of diet fat consumed per day.</dd> <dt><code>fiber</code></dt>
<dd>A numeric vector of grams of fiber consumed per day.</dd> <dt><code>retinol</code></dt>
<dd>A numeric vector of retinol consumed per day.</dd> <dt><code>smoke</code></dt>
<dd>A numeric vector of smoking status (1=Never, 2=Former, 3=Current Smoker).</dd> <dt><code>vituse</code></dt>
<dd>A numeric vector of vitamin use (1=Yes, fairly often, 2=Yes, not often, 3=No).</dd> 
</dl>

Format

A Data Set for Cgam — plasma

<dl>
 <dt><code>logplasma</code></dt>
<dd>A numeric vector of the logarithm of plasma levels.</dd>

 <dt><code>betacaro</code></dt>
<dd>A numeric vector of dietary beta carotene consumed mcg per day.</dd>

 <dt><code>bmi</code></dt>
<dd>A numeric vector of BMI values.</dd>

 <dt><code>cholest</code></dt>
<dd>A numeric vector of cholesterol consumed mg per day.</dd>

 <dt><code>dietfat</code></dt>
<dd>A numeric vector of the logarithm of grams of diet fat consumed per day.</dd>

 <dt><code>fiber</code></dt>
<dd>A numeric vector of grams of fiber consumed per day.</dd>

 <dt><code>retinol</code></dt>
<dd>A numeric vector of retinol consumed per day.</dd>

 <dt><code>smoke</code></dt>
<dd>A numeric vector of smoking status (1=Never, 2=Former, 3=Current Smoker).</dd>

 <dt><code>vituse</code></dt>
<dd>A numeric vector of vitamin use (1=Yes, fairly often, 2=Yes, not often, 3=No).</dd>

 
</dl>

plasma: A Data Set for Cgam

Description

Usage

Arguments

Format

References

Examples