Anuradha Roy, Ph.D.

Professor, Management Science and Statistics

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Anuradha Roy holds a Ph.D. in applied mathematical sciences from Oakland University, Michigan, an M.Stat. (M.S.) in advanced probability and mathematical statistics from Indian Statistical Institute, Calcutta, India, and a B.Sc. (B.S.) in mathematics (with first class honors) from Calcutta University (Presidency College), India.

Professor Roy’s research interests include developing classification rules for multivariate repeated measures data with structured mean vectors and Kronecker structured covariance matrices and the related hypotheses testing procedures. She also works on linear models for multivariate repeated measures data, and also on summary data, namely symbolic data. As an applied statistician she has a passion to work on applied problems. Areas of application include medical and biomedical sciences, and engineering applications. She has been a visiting professor at the KTH Royal Institute of Technology, Stockholm, Sweden and at the Universidade Nova de Lisboa, Caparica, Portugal.

Professor Roy’s research has appeared in numerous journals, including Journal of Multivariate Analysis, Advances in Data Analysis and Classification, Computational Statistics and Data Analysis, Computational Statistics, Journal of Statistical Planning and Inference, Linear Algebra and its Applications, Journal of Computational and Applied Mathematics, Test, Statistics in Medicine, Biometrical Journal, Journal of Biopharmaceutical Statistics , Bone and Journal of Clinical Oncology, as well as in several book chapters.

Professor Roy has presented her research outcomes to many international conferences in many countries, such as the USA, the UK, France, Italy, Spain, Japan, Poland, Portugal, Brazil, Canada, Chile, China, Croatia, Hong Kong, Hungary, Montenegro, Sweden, Switzerland, etc. She has also organized and chaired many invited organized sessions for many international conferences in many countries.

Professor Roy is looking for self-motivated Ph.D. students with strong computing skills to work with her in Multivariate Analysis and Symbolic Data Analysis.

Teaching

  • Multivariate Analysis
  • Linear Models
  • Probability and Statistics

Research Interests

  • Multivariate analysis
  • Multivariate repeated measures data
  • Mixed effects models
  • Symbolic data analysis
  • Kronecker structured covariance matrix

Degrees

  • Ph.D. Oakland University, Michigan
  • M.Stat. (M.S.) Indian Statistical Institute, Calcutta, India
  • B.Sc. (B.S.) Calcutta University (Presidency College), India

Publications

  • “Testing of Multivariate Repeated Measures Data with Block Exchangeable Covariance Structure,” with Žežula I., Klein D., TEST, Vol. 27, Issue 2, 2018, pp. 360-378.
  • “A Comparison of Likelihood Ratio Tests and Rao’s Score Test for Three Separable Covariance Matrix Structures,” with Filipiak K., Klein D., Biometrical Journal, Vol. 59, Issue 1, 2017, pp. 192–215.
  • “Score Test for a Separable Covariance Structure with the First Component as Compound Symmetric Correlation Matrix,” with Filipiak K., Klein D., Journal of Multivariate Analysis, Vol. 150, 2016, pp. 105-124.
  • “Optimal Estimation for Doubly Multivariate Data in Blocked Compound Symmetric Covariance Structure,” with Zmyślony R., Fonseca M. and Leiva R., Journal of Multivariate Analysis, Vol. 144, 2016, pp. 81-90.
  • “Testing of Equality of Mean Vectors for Paired Doubly Multivariate Observations in Blocked Compound Symmetric Covariance Matrix Setup,” with Leiva R., Žežula I. and Klein D., Journal of Multivariate Analysis, Vol. 137, 2015, pp. 50-60.
  • “Linear Discrimination for Three-level Multivariate Data with a Separable Additive Mean Vector and a Doubly Exchangeable Covariance Structure,” with Leiva R., Computational Statistics and Data Analysis, Vol. 56, Issue 6, 2012, pp. 1644-1661.
  • “Linear Discrimination for Multi-level Multivariate Data with Separable Means and Jointly Equicorrelated Covariance Structure,” with Leiva R., Journal of Statistical Planning and Inference, Vol. 141, Issue 5, 2011, pp. 1910-1924.
  • “Classification Rules for Triply Multivariate Data with an AR(1) Correlation Structure on the Repeated Measures over Time,” with Leiva R., 2009, Journal of Statistical Planning and Inference, Vol. 139, Issue 8, 2009, pp. 2598-2613.
  • “Discrimination with Jointly Equicorrelated Multi-level Multivariate Data,” with Leiva R. Advances in Data Analysis and Classification, Vol. 1, Issue 3, 2007, pp. 175-199.
  • “On Discrimination and Classification with Multivariate Repeated Measures Data,” with Khattree R., Journal of Statistical Planning and Inference, Vol. 134, Issue 2, 2005, pp. 462-485.