A powerful penalized multinomial logistic regression approach

Authors

Cornelia Fuetterer (ORCID: https://orcid.org/0000-0002-8354-6660)
Thomas Augustin (ORCID: https://orcid.org/0000-0002-1854-6226)
Ruth M. Pfeiffer (ORCID: https://orcid.org/0000-0001-7791-2698)
Malte Nalenz (ORCID: https://orcid.org/0000-0003-3439-4469)

Institutions

TUM Klinikum (DE)
National Cancer Institute (US)
Ludwig-Maximilians-Universität München (DE)

Publication Details

Journal: Computational Statistics
Published: 2025-05-25
DOI: https://doi.org/10.1007/s00180-025-01635-0
Primary Topic: Statistical Methods and Inference
Type: article
Field-Weighted Citation Impact: 0.00

Funders

Boehringer Ingelheim Fonds
National Institutes of Health

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

A powerful penalized multinomial logistic regression approach

Cornelia Fuetterer, Thomas Augustin, Ruth M. Pfeiffer, Malte Nalenz

May 25, 2025

Computational Statistics

Statistical Methods and Inference

article

A powerful penalized multinomial logistic regression approach

Cornelia Fuetterer, Thomas Augustin, Ruth M. Pfeiffer, Malte Nalenz

May 25, 2025article en

Abstract

No abstract available for this paper.

Computational StatisticsVol. 40(8)

TUM Klinikum (DE), National Cancer Institute (US), Ludwig-Maximilians-Universität München (DE)

Boehringer Ingelheim Fonds, National Institutes of Health

Openalex Percentile: Top 88%

Statistical Methods and Inference

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.