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

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) 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. The package also includes robust and multi-way clustered standard errors.