World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
64
Citations
27566
World Ranking
407
National Ranking
216

Research.com Recognitions

  • 1993 - Fellow of the American Statistical Association (ASA)

Overview

Mike West is affiliated with Duke University in the United States and has contributed extensively to research in decision sciences, with a strong focus on forecasting techniques and Bayesian modeling. Their work spans multiple subfields including management science and operations research, artificial intelligence, marketing, statistics and probability, and general economics, econometrics and finance.

The scientist's main topics of research include:

  • Forecasting Techniques and Applications
  • Bayesian Modeling and Causal Inference
  • Consumer Market Behavior and Pricing
  • Customer Churn and Segmentation
  • Monetary Policy and Economic Impact
  • Decision-Making and Behavioral Economics
  • Market Dynamics and Volatility

Mike West has published consistently in high-impact venues, with frequent publications appearing in:

  • arXiv (Cornell University)
  • Bayesian Analysis
  • Applied Stochastic Models in Business and Industry
  • Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • Journal of the Royal Statistical Society Series C (Applied Statistics)

Recent notable papers include:

  • Bayesian predictive decision synthesis, 2023, Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • Hierarchical dynamic modelling for individualized Bayesian forecasting, 2023, Journal of the Royal Statistical Society Series C (Applied Statistics)
  • Perspectives on Constrained Forecasting, 2023, Bayesian Analysis
  • Adaptive Variable Selection for Sequential Prediction in Multivariate Dynamic Models, 2020, Bayesian Analysis
  • Bayesian Predictive Synthesis with Outcome-Dependent Pools, 2025, Statistical Science

Collaborative work features frequently with co-authors such as Andrew Cron, Anna K. Yanchenko, Graham Tierney, Christoph Hellmayr, and Emily Tallman. Their research partnerships have produced multiple studies with some collaborators appearing in six and five joint publications respectively.

Mike West has been recognized as a Fellow of the American Statistical Association (ASA) since 1993, reflecting involvement and standing within the statistical community.

Best Publications

  • Bayesian Forecasting and Dynamic Models

    Mike West;Jeff Harrison

  • Bayesian Density Estimation and Inference Using Mixtures

    Michael D. Escobar;Mike West

  • Combined Parameter and State Estimation in Simulation-Based Filtering

    Jane Liu;Mike West

  • Bayesian forecasting and dynamic models (2nd ed.)

    Mike West;Jeff Harrison

  • Dynamic Generalized Linear Models and Bayesian Forecasting

    Mike West;P. Jeff Harrison;Helio S. Migon

  • Role for E2F in Control of Both DNA Replication and Mitotic Functions as Revealed from DNA Microarray Analysis

    Seiichi Ishida;Erich Huang;Harry Zuzan;Rainer Spang

  • Bayesian Dynamic Factor Models and Portfolio Allocation

    Omar Aguilar;Mike West

  • Monte Carlo Smoothing for Nonlinear Time Series

    Simon J Godsill;Arnaud Doucet;Mike West

  • High-dimensional sparse factor modeling: Applications in gene expression genomics

    Carlos Marinho Carvalho;Jeffrey Chang;Joseph E. Lucas;Joseph R. Nevins

  • BAYESIAN MODEL ASSESSMENT IN FACTOR ANALYSIS

    Hedibert Freitas Lopes;Mike West

  • Sparse graphical models for exploring gene expression data

    Adrian Dobra;Chris Hans;Beatrix Jones;Joseph R. Nevins

  • Applied Bayesian Forecasting and Times Series Analysis

    Andy Pole;Mike West;Jeff Harrison

  • On scale mixtures of normal distributions

    Mike West

  • Bayesian Inference on Network Traffic Using Link Count Data

    Claudia Tebaldi;Mike West

  • Approximating posterior distributions by mixtures

    Mike West

  • Time Series: Modeling, Computation, and Inference

    Raquel Prado;Mike West

  • Bayesian curve fitting using multivariate normal mixtures

    Peter Muller;Alaattin Erkanli;Mike West

  • On Bayesian analysis of mixtures with an unknown number of components. Discussion. Author's reply

    S. Richardson;P. J. Green;C. P. Robert;M. Aitkin

  • Experiments in Stochastic Computation for High-Dimensional Graphical Models

    Beatrix Jones;Carlos Carvalho;Adrian Dobra;Chris Hans

  • Shotgun Stochastic Search for “Large p” Regression

    Chris Hans;Adrian Dobra;Mike West

Frequent Co-Authors

Joseph R. Nevins
Joseph R. Nevins Duke University
Jeffrey R. Marks
Jeffrey R. Marks Duke University
Andrew Berchuck
Andrew Berchuck Duke University
Adrian F. M. Smith
Adrian F. M. Smith Imperial College London
Simon J. Godsill
Simon J. Godsill University of Cambridge
Arnaud Doucet
Arnaud Doucet University of Oxford
Jen-Tsan Chi
Jen-Tsan Chi Duke University
Lingchong You
Lingchong You Duke University
Jeffrey T. Chang
Jeffrey T. Chang The University of Texas Health Science Center at Houston

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