4 papers
Asymptotics of Nonparametric Estimation under General Non-monotone MAR Missingness: A Nonparametric Maximum Likelihood Approach
Yating Zou, Huimin Hu, Jeffrey Näf
Missing data constitute a pervasive challenge in empirical research. Consequently, there is an ever-growing number of methods designed to address this challenge, with multiple impu…
Generative Modeling under Non-Monotone MAR Missingness via Approximate Wasserstein Gradient Flows
Gitte Kremling, Jeffrey Näf, Johannes Lederer
The prevalence of missing values in data science poses a substantial risk to any further analyses. Despite a wealth of research, principled nonparametric methods to deal with gener…
CLVAE: A Variational Autoencoder for Long-Term Customer Revenue Forecasting
Jeffrey Näf, Riana Valera Mbelson, Markus Meierer
Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual settings, yet existing approaches…
Asymptotics of Nonparametric Estimation under general non-monotone MAR missingness: A Bayesian Approach
Badr-Eddine Chérief-Abdellatif, Jeffrey Näf
Missing values are ubiquitous in statistical practice, with potentially detrimental consequences for any statistical analysis. As such, a wealth of methods and theoretical results…