predict.B2mix

Predict Method for Binomial Mixtures

nonparametric

Kiefer-Wolfowitz maximum likelihood estimation for mixture models
and some other density estimation and regression methods based on convex
optimization. See Koenker and Gu (2017) REBayes: An R Package for Empirical
Bayes Mixture Methods, Journal of Statistical Software, 82, 1--26,
<DOI:10.18637/jss.v082.i08>.

Roger Koenker

REBayes

Empirical Bayes Estimation and Inference

Jiaying Gu

Ivan Mizera

predict.B2mix function

<dl><dt>object</dt>
<dd>fitted object of class "B2mix"</dd>
<dt>newdata</dt>
<dd>Values at which prediction is desired an n by 2 matrix</dd>
<dt>Loss</dt>
<dd>Loss function used to generate prediction: Currently supported values:
2 to get mean predictions, 1 to get median predictions, 0 to get modal predictions
or any tau in (0,1) to get tau-th quantile predictions.</dd>
<dt>newk</dt>
<dd>k values (number of trials) for the predictions an n by 2 matrix</dd>
<dt>...</dt>
<dd>optional arguments to predict</dd></dl>

Arguments

Author

Predict Method for Bmix — predict.B2mix

<dl>

<dt>object</dt>
<dd>fitted object of class "B2mix"</dd>


<dt>newdata</dt>
<dd>Values at which prediction is desired an n by 2 matrix</dd>


<dt>Loss</dt>
<dd>Loss function used to generate prediction: Currently supported values:
2 to get mean predictions, 1 to get median predictions, 0 to get modal predictions
or any tau in (0,1) to get tau-th quantile predictions.</dd>


<dt>newk</dt>
<dd>k values (number of trials) for the predictions an n by 2 matrix</dd>


<dt>...</dt>
<dd>optional arguments to predict</dd>

</dl>

predict.B2mix: Predict Method for Bmix

Description

Usage

Value

Arguments

Author

Details