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Jeffrey Naf

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author1
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • stat.ME2
  • stat.AP1
  • stat.CO1

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

stat.AP2026

A Practical Guide to Modern Imputation

Jeffrey Näf

This guide based on recent papers should help researchers avoid some of the most common pitfalls of missing value imputation imputation.

stat.CO2025

Do we Need Dozens of Methods for Real World Missing Value Imputation?

Krystyna Grzesiak, Christophe Muller, Julie Josse +1

Missing values pose a persistent challenge in modern data science. Consequently, there is an ever-growing number of publications introducing new imputation methods in various field…

stat.ME2025

How to rank imputation methods?

Jeffrey Näf, Krystyna Grzesiak, Erwan Scornet

Imputation is an attractive tool for dealing with the widespread issue of missing values. Consequently, studying and developing imputation methods has been an active field of resea…

stat.ME2025

Parametric MMD Estimation with Missing Values: Robustness to Missingness and Data Model Misspecification

Badr-Eddine Chérief-Abdellatif, Jeffrey Näf

In the missing data literature, the Maximum Likelihood Estimator (MLE) is celebrated for its ignorability property under missing at random (MAR) data. However, its sensitivity to m…

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