predict.feglm

<code>predict.feglm</code> is a generic function which obtains predictions from an object 
returned by <code>feglm</code>.

Provides a routine to partial out factors with many levels during the optimization of the log-likelihood function of the corresponding generalized linear model (glm). The package is based on the algorithm described in Stammann (2018) <doi:10.48550/arXiv.1707.01815> and is restricted to glm's that are based on maximum likelihood estimation and nonlinear. It also offers an efficient algorithm to recover estimates of the fixed effects in a post-estimation routine and includes robust and multi-way clustered standard errors. Further the package provides analytical bias corrections for binary choice models derived by Fernandez-Val and Weidner (2016) <doi:10.1016/j.jeconom.2015.12.014> and Hinz, Stammann, and Wanner (2020) <doi:10.48550/arXiv.2004.12655>.

Amrei Stammann

alpaca

Fit GLM's with High-Dimensional k-Way Fixed Effects

Daniel Czarnowske

predict.feglm function

<dl><dt>object</dt>
<dd>an object of class <code>"feglm"</code>.</dd>
<dt>type</dt>
<dd>the type of prediction required. <code>"link"</code> is on the scale of the linear predictor
whereas <code>"response"</code> is on the scale of the response variable. Default is <code>"link"</code>.</dd>
<dt>...</dt>
<dd>other arguments.</dd></dl>

Arguments

Predict method for feglm fits — predict.feglm

<dl>

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


<dt>type</dt>
<dd>the type of prediction required. <code>"link"</code> is on the scale of the linear predictor
whereas <code>"response"</code> is on the scale of the response variable. Default is <code>"link"</code>.</dd>


<dt>...</dt>
<dd>other arguments.</dd>

</dl>

predict.feglm: Predict method for `feglm` fits

Description

Usage

Value

Arguments

See Also