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Mathematics

D-Index
49
Citations
11885
World Ranking
1131
National Ranking
517

Overview

Peter Müller is affiliated with The University of Texas at Austin in the United States. Their research primarily spans the fields of Mathematics and Computer Science, with a strong focus on Statistics and Probability as well as Artificial Intelligence. Subfields also include Cancer Research, Management Science and Operations Research, and Radiology, Nuclear Medicine and Imaging.

The main topics of their scholarly work concentrate on Bayesian Methods and Mixture Models, Statistical Methods and Inference, and Statistical Methods in Clinical Trials. Other notable topics include Statistical Methods and Bayesian Inference, Advanced Clustering Algorithms Research, Advanced Causal Inference Techniques, and Cancer Genomics and Diagnostics.

Frequent publication venues for Peter Müller include:

  • arXiv (Cornell University)
  • Journal of Computational and Graphical Statistics
  • Bayesian Analysis
  • Biometrics
  • Pharmaceutical Statistics

Frequent coauthors of this researcher are:

  • Yuan Ji
  • Abhra Sarkar
  • Giorgio Paulon
  • Apostolia M. Tsimberidou
  • Noirrit Kiran Chandra

Recent papers authored or coauthored by Peter Müller include:

  • "Search Algorithms and Loss Functions for Bayesian Clustering," 2022, Journal of Computational and Graphical Statistics
  • "Innovative trial design in precision oncology," 2020, Seminars in Cancer Biology
  • "A Bayesian nonparametric approach for evaluating the causal effect of treatment in randomized trials with semi-competing risks," 2020, Biostatistics
  • "Consensus Monte Carlo for Random Subsets Using Shared Anchors," 2020, Journal of Computational and Graphical Statistics
  • "Editorial: Roles of Hypothesis Testing, p-Values and Decision Making in Biopharmaceutical Research," 2021, Statistics in Biopharmaceutical Research

Best Publications

  • Estimating mixture of dirichlet process models

    Steven N. Maceachern;Peter Müller

  • Portfolio selection with higher moments

    Campbell R. Harvey;John C. Liechty;Merrill W. Liechty;Peter Müller

  • Nonparametric Bayesian data analysis

    Peter Müller;Fernando A Quintana

  • An ANOVA model for dependent random measures

    Maria De Iorio;Peter Müller;Gary L Rosner;Steven N MacEachern

  • Bayesian curve fitting using multivariate normal mixtures

    Peter Muller;Alaattin Erkanli;Mike West

  • Simulation Based Optimal Design

    Peter Müller

  • Optimal Sample Size for Multiple Testing: the Case of Gene Expression Microarrays

    Peter Müller;Giovanni Parmigiani;Christian P. Robert;Judith Rousseau

  • Dynamic models for spatiotemporal data

    Jonathan R. Stroud;Peter Müller;Bruno Sansó

  • Determining the effective sample size of a parametric prior

    Satoshi Morita;Peter F. Thall;Peter Müller

  • Hierarchical priors and mixture models, with applications in regression and density estimation

    Mike West;Peter Müller;Michael D Escobar;Peter M Uller

  • DPpackage: Bayesian Semi- and Nonparametric Modeling in R

    Alejandro Jara;Timothy E. Hanson;Fernando A. Quintana;Peter Müller

  • FDR and Bayesian Multiple Comparisons Rules

    Peter Muller;Giovanni Parmigiani;Kenneth Rice

  • Bayesian Nonparametrics: Subject index

    Nils Lid Hjort;Chris Holmes;Peter Müller;Stephen G. Walker

  • A Bayesian mixture model for differential gene expression

    Kim Anh Do;Peter Müller;Feng Tang

  • Optimal Bayesian Design by Inhomogeneous Markov Chain Simulation

    Peter Müller;Bruno Sansó;Bruno Sansó;Maria De Iorio

  • INCORPORATING MULTIPLE SOURCES OF STOCHASTICITY INTO DYNAMIC POPULATION MODELS

    Catherine Calder;Michael Lavine;Peter Müller;Peter Müller;James S. Clark

  • A method for combining inference across related nonparametric Bayesian models

    Peter Müller;Fernando Quintana;Gary Rosner

  • Bayesian nonparametric nonproportional hazards survival modeling.

    Maria De Iorio;Wesley O. Johnson;Peter Müller;Gary L. Rosner

  • Adaptive Bayesian Designs for Dose-Ranging Drug Trials

    Donald A. Berry;Peter Müller;Andy P. Grieve;Michael Smith

  • Issues in Bayesian analysis of neural network models

    Peter Müller;David Rios Insua

Frequent Co-Authors

Dipak K. Dey
Dipak K. Dey University of Connecticut
Ming-Hui Chen
Ming-Hui Chen University of Connecticut
Giovanni Parmigiani
Giovanni Parmigiani Harvard University
Bradley P. Carlin
Bradley P. Carlin University of Minnesota
Peter F. Thall
Peter F. Thall The University of Texas MD Anderson Cancer Center
J. Jack Lee
J. Jack Lee The University of Texas MD Anderson Cancer Center
Kim Anh Do
Kim Anh Do The University of Texas MD Anderson Cancer Center
Satoshi Morita
Satoshi Morita Kyoto University
Donald A. Berry
Donald A. Berry The University of Texas MD Anderson Cancer Center
Brani Vidakovic
Brani Vidakovic Georgia Institute of Technology

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