predict.feglm

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

object

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>.

type

<code><a rd-options="" href="/link/predict.feglm?package=alpaca&version=0.3.1" data-mini-rdoc="alpaca::predict.feglm">predict.feglm</a></code> is a generic function which obtains predictions from an object 
returned by <code><a rd-options="" href="/link/feglm?package=alpaca&version=0.3.1" data-mini-rdoc="alpaca::feglm">feglm</a></code>.

Provides a routine to concentrate 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 proposed by Stammann (2018) <arXiv:1707.01815> and is
restricted to glm's that are based on maximum likelihood estimation and non-linear. 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 an
analytical bias-correction for binary choice models (logit and probit) derived by Fernandez-Val
and Weidner (2016) <doi:10.1016/j.jeconom.2015.12.014>.

Amrei Stammann

alpaca

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

Daniel Czarnowske

predict.feglm function

<code><a rd-options='' href='predict.feglm'>predict.feglm</a></code> is a generic function which obtains predictions from an object 
returned by <code><a rd-options='' href='feglm'>feglm</a></code>.

predict.feglm: Predict method for `feglm` fits

Description

Usage

Arguments

Value

See Also