Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Bhandari, Subir Kumar"'
Autor:
Dey, Monitirtha, Bhandari, Subir Kumar
Simultaneous statistical inference has been a cornerstone in the statistics methodology literature because of its fundamental theory and paramount applications. The mainstream multiple testing literature has traditionally considered two frameworks: t
Externí odkaz:
http://arxiv.org/abs/2309.16657
In modern scientific experiments, we frequently encounter data that have large dimensions, and in some experiments, such high dimensional data arrive sequentially rather than full data being available all at a time. We develop multiple testing proced
Externí odkaz:
http://arxiv.org/abs/2306.05315
Autor:
Roy, Rahul, Bhandari, Subir Kumar
Here we address dependence among the test statistics in connection with asymptotically Bayes' optimal tests in presence of sparse alternatives. Extending the setup in Bogdan et.al. (2011) we consider an equicorrelated ( with equal correlation $\rho$
Externí odkaz:
http://arxiv.org/abs/2208.11924
Autor:
Dey, Monitirtha, Bhandari, Subir Kumar
Familywise error rate (FWER) has been a cornerstone in simultaneous inference for decades, and the classical Bonferroni method has been one of the most prominent frequentist approaches for controlling FWER. The present article studies the limiting be
Externí odkaz:
http://arxiv.org/abs/2110.05070
Autor:
Das, Nabaneet, Bhandari, Subir Kumar
In this paper, we have attempted to study the behaviour of the family wise error rate (FWER) for Bonferroni's procedure and false discovery rate (FDR) of the Benjamini-Hodgeberg procedure for simultaneous testing problem with equicorrelated normal ob
Externí odkaz:
http://arxiv.org/abs/2008.08366
Autor:
Roy, Rahul, Bhandari, Subir Kumar
In this paper we explore the behaviour of dependent test statistics for testing of multiple hypothesis . To keep simplicity, we have considered a mixture normal model with equicorrelated correlation set up. With a simple linear transformation,the tes
Externí odkaz:
http://arxiv.org/abs/2001.02229
Autor:
Dey, Monitirtha1 (AUTHOR) monitirthadey3@gmail.com, Bhandari, Subir Kumar1 (AUTHOR)
Publikováno v:
Statistical Papers. Jun2024, Vol. 65 Issue 4, p2313-2326. 14p.
In this paper our aim is to characterize the set of extreme points of the set of all n-dimensional copulas (n > 1). We have shown that a copula must induce a singular measure with respect to Lebesgue measure in order to be an extreme point in the set
Externí odkaz:
http://arxiv.org/abs/1709.02472
Autor:
Kundu, Anupam, Bhandari, Subir Kumar
Given two sets of training samples, general method is to estimate the density function and classify the test sample according to higher values of estimated densities. Natural way to estimate the density should be histogram tending to frequency curve.
Externí odkaz:
http://arxiv.org/abs/1706.09828
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.