predict.crch.boost

an object of class <code>"crch.boost"</code>.

object

an optional data frame in which to look for variables with
 which to predict.

newdata

stopping iteration. Can be either a character (<code>"max"</code>, 
 <code>"aic"</code>, <code>"bic"</code>, <code>"cv"</code>) or a numeric value. If not <code>NULL</code>,
 newdata has to be supplied.

mstop

further arguments passed to or from other methods.

&#8230;

Obtains various types of predictions for <code>crch.boost</code> models.

regression

Different approaches to censored or truncated regression with
conditional heteroscedasticity are provided. First, continuous
distributions can be used for the (right and/or left censored or truncated)
response with separate linear predictors for the mean and variance.
Second, cumulative link models for ordinal data
(obtained by interval-censoring continuous data) can be employed for
heteroscedastic extended logistic regression (HXLR). In the latter type of
models, the intercepts depend on the thresholds that define the intervals.

Jakob Messner

crch

Censored Regression with Conditional Heteroscedasticity

Achim Zeileis

Reto Stauffer

predict.crch.boost function

<dl> <dt>object</dt>
<dd>an object of class <code>"crch.boost"</code>.</dd> <dt>newdata</dt>
<dd>an optional data frame in which to look for variables with
 which to predict.</dd> <dt>mstop</dt>
<dd>stopping iteration. Can be either a character (<code>"max"</code>, 
 <code>"aic"</code>, <code>"bic"</code>, <code>"cv"</code>) or a numeric value. If not <code>NULL</code>,
 newdata has to be supplied.</dd> <dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Predicted/Fitted Values for boosted CRCH Fits — predict.crch.boost

<dl>

 <dt>object</dt>
<dd>an object of class <code>"crch.boost"</code>.</dd>

 <dt>newdata</dt>
<dd>an optional data frame in which to look for variables with
 which to predict.</dd>

 <dt>mstop</dt>
<dd>stopping iteration. Can be either a character (<code>"max"</code>, 
 <code>"aic"</code>, <code>"bic"</code>, <code>"cv"</code>) or a numeric value. If not <code>NULL</code>,
 newdata has to be supplied.</dd>

 <dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

predict.crch.boost: Predicted/Fitted Values for boosted CRCH Fits

Description

Usage

Value

Arguments

See Also