Paper: Robust logistic quantile regression models using skewed heavy-tailed distributions

Paper: Modelling time series of counts with deflation or inflation of zeros

Paper: Intra household resource allocation and gender relation in Côte d’Ivoire : a way for facing non inclusive growth situation

Paper: Modeling the Financial Market Indicators with Semiparametric Volatility Model with Varying Frequency

Paper: Prediction Interval of Air Pollutants Concentration by Nonparametric Regression Analysis

Paper: Prediction Interval of Air Pollutants Concentration by Nonparametric Regression Analysis

He is selected as the recipient of the 2021 ISI Founders of Statistics Prize for his 1996 paper on ‘Regression Shrinkage and Selection via the LASSO’, published in the Journal of the Royal Statistical Society Series B, pp. 267-288. Robert Tibshirani is Professor of Biomedical Science and Statistics at Stanford University.

The Lasso paper (Tibshirani, 1996) has had 37,360 citations as of late January 2021 indicating its wide influence across statistics, data science, computer science and broadly in Science, Business and Economics. As we are faced with large and more complex data sets, the Lasso will continue to provide the basic underpinning for developments to handle such data. One reason for the paper’s impact is the clarity with which the paper is written with thorough and clear explanations of the method both analytically and geometrically. In statistics, biostatistics and machine learning, the Lasso (least absolute shrinkage and selection operator) is a regression analysis method that performs both variable selection and regularization in order to enhance the prediction accuracy and interpretability of the resulting statistical model. The Lasso is really the cornerstone of many modern methods of statistics and data science.

The contribution recognized by the Founders of Statistics Prize must be a research article or book published within the last three decades. Each Founders of Statistics (formerly known as Karl Pearson Prize) Award selection committee comprises renowned statisticians from across the world. The prize is given biennially, at the ISI World Statistics Congress (WSC), starting with the WSC in Hong Kong in August 2013. ISI is grateful to Elsevier Publishers for their ongoing sponsorship of the Prize.

The 2017 ISI Mahalanobis Award Selection Committee emphasized Prof. Mukerjee’s lifetime record of truly outstanding research in design of experiments and asymptotic theory of statistical inference, and significant research in survey sampling; his considerable professional service, including editorial boards for extended periods on some major statistical journals; and his teaching and mentoring which has contributed greatly to capacity development in a large developing country.

Prof. Mukerjee has authored or co-authored five books and published over 240 papers, many in major statistical journals including the Annals of Statistics, Biometrika, Journal of the Royal Statistical Society B, Statistica Sinica and Sankhya, the Indian statistics journal founded by Professor Mahalanobis. He has collaborated with several of the leading researchers in statistics worldwide. In the area of design of experiments, he is a leading expert on orthogonal array designs, diallel crosses, and fractional factorial plans. In asymptotic theory, he is the leading expert in the world in the area of probability matching priors, and on the use of the Bayesian shrinkage argument for obtaining asymptotic results. His original contributions to the methods and theory of sample surveys have found appeal in diverse fields.

Prof. Mukherjee also provided exceptional leadership in India through service to the Indian Official Statistics System as a member of the National Statistical Commission, the Indian Statistical Institute, University Grants Commission and the Agricultural Statistics Research Program. He has contributed significantly in neighbouring developing countries in promoting statistics and modernizing curricula in statistical science.

The award was presented on 21 July 2017 at the ISI World Statistics Congress in Marrakech and was followed by the presentation by Prof. Mukherjee of the Mahalanobis Prize Lecture, titled Research in experimental design in India: achievements and emerging challenges.

Professor Arellano-Valle, Department of Statistics, Pontificia Universidad Católica de Chile, has made outstanding contributions to Statistics in a developing country and region, as an academic leader, in professional leadership and as an inspiration and capacity-builder. His lifetime achievements in statistics (especially in developing countries), and promotion of best statistical practices truly reflect the spirit of the work of Professor P.C. Mahalanobis.

Professor Arellano-Valle is a long-time academic leader in Statistics in Chile and in South America. His contributions have been immense and diverse, especially so in multivariate analysis, skewed models, multivariate modelling, measurement error models, ordered data analysis, and statistical inference based in flexible models. His work in multivariate statistics, notably as a global leader in elliptically contoured distributions and skew-elliptical distributions, is particularly apt in memory of Professor P.C. Mahalanobis who made so many seminal contributions to multivariate statistics. In addition, in his advancement of research, Professor Arellano-Valle has systematically pursued collaboration, always involving others, very often junior people, offering guidance, ideas and encouragement. This style of work is reflected in the vast number of co-authors of his many papers, many being former students of his.

Professor Arellano-Valle is an inspiration and capacity-builder in Statistics. He is a very sought-after advisor and has trained and inspired a large number of students of different nationalities, both at the M.S. and Ph.D. levels, who have taken jobs in academia, government, and in industry. He is also well known for his inspiring teaching at all levels. He is regarded as the mentor and the cultural leader by many statisticians in a considerable portion of South America, especially but not only of the younger generations. Moreover, his ties with scientists from Europe, North America and, more recently, Central Asia have provided links with other environments, facilitating the interaction between South America and the world.