A Conversation with Shoutir Kishore Chatterjee
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Shoutir Kishore Chatterjee (SKC) as mentioned in this paper was the National Lecturer in Statistics (1985--1986) of the University Grants Commission, India, the President of the Section of Statistics of the Indian Science Congress (1989) and an Emeritus Scientist (1997--2000) of Council of Scientific and Industrial Research, India.Abstract:
Shoutir Kishore Chatterjee was born in Ranchi, a small hill station in India, on November 6, 1934. He received his B.Sc. in statistics from the Presidency College, Calcutta, in 1954, and M.Sc. and Ph.D. degrees in statistics from the University of Calcutta in 1956 and 1962, respectively. He was appointed a lecturer in the Department of Statistics, University of Calcutta, in 1960 and was a member of its faculty until his retirement as a professor in 1997. Indeed, from the 1970s he steered the teaching and research activities of the department for the next three decades. Professor Chatterjee was the National Lecturer in Statistics (1985--1986) of the University Grants Commission, India, the President of the Section of Statistics of the Indian Science Congress (1989) and an Emeritus Scientist (1997--2000) of the Council of Scientific and Industrial Research, India. Professor Chatterjee, affectionately known as SKC to his students and admirers, is a truly exceptional person who embodies the spirit of eternal India. He firmly believes that ``fulfillment in man's life does not come from amassing a lot of money, after the threshold of what is required for achieving a decent living is crossed. It does not come even from peer recognition for intellectual achievements. Of course, one has to work and toil a lot before one realizes these facts.''read more
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Nonparametric Testing Under Progressive Censoring
TL;DR: In this article, a general class of rank order tests for progressive censoring is proposed along with a basic martinga:le property and a Brownian motion approximation for a related rank order process, asymptotic distribution theory of the proposed statistics is developed.
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Non-Parametric Tests for the Bivariate Two-Sample Location Problem:
TL;DR: In this article, the Wilcoxon-Mann-Whitney rank-sum test and Mood's median test for the univariate two-sample location problem were extended to the case of two variables, following a cond...
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On Birnbaum's Theorem on the Relation between Sufficiency, Conditionality and Likelihood
TL;DR: If the conditioning variable is required to depend only on the value of the minimal sufficient statistic, Birnbaum's proof fails as mentioned in this paper, and it is shown that this condition fails.
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A Bivariate Sign Test for Location
TL;DR: In this article, a strictly distribution-free test has been proposed for testing that several independent pairs of random variables have locations as specified, and the test statistic has asymptotically a chi-square distribution with degrees of freedom two.