dataAugmentation

<p>This function performs data augmentation on the provided dataset.</p>

internal

Fits generalized linear models (GLMs) when there is missing data in both the response and categorical covariates. The functions implement likelihood-based methods using the Expectation and Maximization (EM) algorithm and optionally apply Firth’s bias correction for improved inference. See Pradhan, Nychka, and Bandyopadhyay (2025) <https:>, Maiti and Pradhan (2009) <doi:10.1111/j.1541-0420.2008.01186.x>, Maity, Pradhan, and Das (2019) <doi:10.1080/00031305.2017.1407359> for further methodological details.

Vivek Pradhan

glmfitmiss

Fitting GLMs with Missing Data in Both Responses and Covariates

Douglas Nychka

Soutir Bandyopadhyay

dataAugmentation function

Data Augmentation Function — dataAugmentation

Data Augmentation Function

dataAugmentation: Data Augmentation Function

Description

Usage

Arguments