P
Pranab Kumar Sen
Researcher at University of North Carolina at Chapel Hill
Publications - 572
Citations - 23008
Pranab Kumar Sen is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Estimator & Nonparametric statistics. The author has an hindex of 51, co-authored 570 publications receiving 19997 citations. Previous affiliations of Pranab Kumar Sen include Indian Statistical Institute & Academia Sinica.
Papers
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Journal ArticleDOI
Smooth estimation of multivariate survival and density functions
TL;DR: By considering a multivariate version of the Hille's theorem, the technique developed by Chaubey and Sen (Statist. Decisions 14 (1996) 1) is extended for estimating a multiivariate survival distribution and its associated density.
The mean-median-mode inequality and noncentral chi square distributions*
TL;DR: In this article, the usual ordering of the mean, median and mode for a central chi square distribution is extended for the noncentral case, and it is shown that both the median and the mode are sub-additive with respect to the non centrality parameter.
Journal ArticleDOI
On some sequential simultaneous confidence intervals procedures
TL;DR: In this article, the authors extend the simultaneous confidence intervals procedures (SCIP) along the lines of Chow and Robbins [3] and develop certain robust non-parametric SCIP based on the results of Sen [10] and Sen and Ghosh [11]; the allied efficiency results are also presented.
Book ChapterDOI
Paired comparisons for multiple characteristics: An Anocova approach
TL;DR: In this article, an analysis of covariance model is developed for paired comparisons to situations in which responses (on a preference order) to paired comparisons are obtained on some primary as well as concomitant traits.
Posted Content
A Robust Version of the KPSS Test Based on Ranks
TL;DR: In this article, the authors proposed a test of the null hypothesis of stationarity that is robust to the presence of fat-tailed errors, which is a modified version of the KPSS statistic in which ranks substitute the original observations.