2026 Thomas P. Hettmansperger: Mathematics Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Mathematics	36	2622	2339	1080	906	127	6217

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Mathematics

2622

2339

1080

906

127

6217

Research.com Recognitions

1986 - Fellow of the American Statistical Association (ASA)

Overview

Thomas P. Hettmansperger is affiliated with Pennsylvania State University in the United States. Their research spans several areas within statistical sciences and decision sciences.

Their recent publication record includes the paper titled A bivariate test for location based on simplicial depth, published in 2020 within the journal Communication in Statistics- Theory and Methods. This publication has received citations and reflects their engagement with advanced statistical methodologies.

In collaboration, Thomas P. Hettmansperger has worked with coauthor:

Timothy J. Killeen

Their research has appeared predominantly in the venue:

Communication in Statistics- Theory and Methods

Their work covers main fields of study such as:

Decision Sciences
Mathematics

With subfields including:

Statistics and Probability
Management Science and Operations Research
Statistics, Probability and Uncertainty

The key topics of their research focus on:

Advanced Statistical Methods and Models
Optimal Experimental Design Methods
Advanced Statistical Process Monitoring

Thomas P. Hettmansperger was recognized as a Fellow of the American Statistical Association (ASA) in 1986.

Best Publications

Statistical inference based on ranks

Thomas P. Hettmansperger;Joseph W. McKean

989
Citations
Robust Nonparametric Statistical Methods

Thomas P. Hettmansperger;Joseph W. McKean

776
Citations
A practical affine equivariant multivariate median

Thomas P. Hettmansperger;Ronald H. Randles

214
Citations
Robust analysis of variance based upon a likelihood ratio criterion

Ronald M. Schrader;Thomas P. Hettmansperger

209
Citations
A Bounded Influence, High Breakdown, Efficient Regression Estimator

Unknown

184
Citations
A Cautionary Note on the Method of Least Median Squares

Thomas P. Hettmansperger;Simon J. Sheather

165
Citations
Inference for mixtures of symmetric distributions

David R. Hunter;Shaoli Wang;Thomas P. Hettmansperger

149
Citations
Confidence intervals based on interpolated order statistics

Thomas P Hettmansperger;Thomas P Hettmansperger;Simon J Sheather

133
Citations
Tests of hypotheses based on ranks in the general linear model

Joseph W. McKean;Thomas P. Hettmansperger

124
Citations
A Robust Alternative Based on Ranks to Least Squares in Analyzing Linear Models

Thomas P. Hettmansperger;Joseph W. McKean

119
Citations
Affine Invariant Rank Methods in the Bivariate Location Model

B. M. Brown;T. P. Hettmansperger

119
Citations
The ranked-set sample sign test

Thomas P. Hettmansperger

118
Citations
Affine Invariant Multivariate Multisample Sign Tests

Thomas P. Hettmansperger;Jukka Nyblom;Hannu Oja

111
Citations
Tests for Patterned Alternatives in k-Sample Problems

Thomas P. Hettmansperger;Robert M. Norton

111
Citations
An Affine Invariant Bivariate Version of the Sign Test

B M Brown;Thomas P Hettmansperger

111
Citations
A robust analysis of the general linear model based on one step R-estimates

Joseph W. Mckean;Thomas P. Hettmansperger

109
Citations
A Class of Non-Parametric Tests for Homogeneity Against Ordered Alternatives

Peter V. Tryon;Thomas P. Hettmansperger

107
Citations
Bounded influence rank regression

J. D. Naranjo;T. P. Hettmansperger

93
Citations
A Geometric Interpretation of Inferences Based on Ranks in the Linear Model

Thomas P. Hettmansperger;Joseph W. McKean

83
Citations
Almost nonparametric inference for repeated measures in mixture models

T. P. Hettmansperger;Hoben Thomas

77
Citations
Two‐Sample Inference Based on One‐Sample Sign Statistics

Thomas P. Hettmansperger

25
Citations
Nonparametric Methods in General Linear Models.

Thomas P. Hettmansperger;Madan L. Puri;Pranab K. Sen

2
Citations

Frequent Co-Authors

Simon J. Sheather University of Kentucky

Hannu Oja University of Turku

Jane-Ling Wang University of California, Davis

Dennis K. J. Lin Purdue University West Lafayette

George Casella University of Florida

Pranab Kumar Sen University of North Carolina at Chapel Hill

Madan L. Puri Indiana University

Ingrid Van Keilegom KU Leuven

External Links

Personal website of Thomas P. Hettmansperger

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