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Showing papers by "Pranab Kumar Sen published in 2005"


Journal ArticleDOI
TL;DR: In this paper, the problem of homogeneity among groups by comparison of genomic sequences is considered, and a one-sided hypothesis test is considered and the classical ANOVA decomposition can be directly adapted to sample measures based on the Hamming distance, without necessarily going through their second moments.

45 citations


Posted Content
TL;DR: In this article, the role of Hamming distance based analysis is appraised in this context and the MANOVA decomposability aspects are specially appraised. The Hamming Distance incorporates the idea of Gini-Simpson diversity index in a variety of multidimensional setups, without making very stringent structural regularity assumptions.
Abstract: The celebrated Gini(-Simpson) biodiversity index has found very useful applications in ecology, bio-environmetrics, econometry, psychometry, genetics, and lately in bioinformatics as well. In such applications, mostly, categorical data models, without possibly an ordering of the categories, crop up, which may preempt routine use of conventional measures of quantitative diversity analysis. Further, in real life problems, mostly, genuine multidimensional data models are encountered. The Hamming distance incorporates the idea of Gini-Simpson diversity index in a variety of multidimensional setups, without making very stringent structural regularity assumptions. In bioinformatics as well as many other large biological system analysis studies, the curse of dimensionality (arising in multidimensional purely qualitative categorical data models) is a geneuine concern. The role of Hamming distance based analysis is appraised in this context. Subgroup or MANOVA decomposability aspects are specially appraised in this setup.

21 citations


Reference EntryDOI
15 Jul 2005
TL;DR: In this article, the rank-permutation principle is applied to the multivariate case and allows for distribution-freeness of a large class of rank statistics, such as the median and rank sum tests.
Abstract: Univariate nonparametric procedures are extended to multivariate nonparametric procedures via the rank-permutation principle. Univariate nonparametric procedures, such as the Wilcoxon signed-rank test and ANCOVA, are reviewed. From this, expansion to the multivariate case is shown through emphasis on the rank-permutation principle. This principle, based on the assets of a conditional procedure that renders conditionally distribution-free properties, is applied to the multivariate case and allows for distribution-freeness of a large class of rank statistics, such as the median and rank sum tests. This then carries into the development of multivariate multisample median tests and multivariate rank sum tests, such as the multivariate signed-rank test. Furthermore, application of the principle is also used in the development of rank MANCOVA, the multivariate extension of ANCOVA. Keywords: nonparametric; univariate; multivariate; rank-permutation; Wilcoxon signed-rank test; Spearmann's rank correlation coefficient; rank MANCOVA; distribution-freeness

12 citations


Journal ArticleDOI
TL;DR: In this article, the union intersection principle was used for hypothesis testing of nonlinear functions of parameters against functional ordered alternatives, and it was shown that the Union intersection principle may have certain advantages over the likelihood principle or its ramifications.

10 citations


01 Jan 2005
TL;DR: Nonparametric inference for ordered measures of diversity and co-diversity in genomics is considered, and their applications stressed.
Abstract: summary In genomics (SNP and RNA amino acid studies), typically, we encounter enormously large dimensional qualitative categorical data models without an ordering of the categories, thus preempting the use of conventional measures of dispersion (variation or diversity) as well as other measures which assume some latent trait variable(s). The Gini-Simpson diversity measure, often advocated for diversity analysis in one-dimensional models, has been adapted to formulate measures of diversity and co-diversity based on the Hamming distance in the multidimensional setup. Based on certain (molecular) biologically interpretable monotone diversity perspectives, an ordering of the Gini-Simpson measures across the genome (positions) is formulated in a meaningful way. Motivated by this feature, nonparametric inference for such ordered measures is considered here, and their applications stressed.

2 citations


Journal ArticleDOI
TL;DR: For some of these nondegradation stochas- tic processes, associated aging perspectives are appraised, without being confined to a semiparametric fashion, and their application in health related quality of life assessment are considered.
Abstract: In a stochastic environment, a degradation process, inspite of showing a mono- tone trend, may contain stochastic variations which may camouflage the statistical picture to a certain extent. There are, however, some other processes which may not exhibit a degradation phenomenon. For some of these nondegradation stochas- tic processes, associated aging perspectives are appraised, without being confined to a semiparametric fashion, and their application in health related quality of life assessment are considered.

1 citations


Journal ArticleDOI
01 Dec 2005-Extremes
TL;DR: The methodology is validated with derivation of asymptotic distribution of the maximum of profile scores, even under weakly dependence conditions, and simulation studies show the proposed method is adequate for moderate sample sizes.
Abstract: Because similarities in biological sequences often suggest similarities in structures and functions, profile searches using multiple alignment of families of related biological sequences provide useful hints for starting points for experimental investigations in molecular biology. Strategies are formulated for determining statistical significance of scores obtained by searching multiple alignment profiles with databanks, while accommodating for gaps in the profile. The methodology is validated with derivation of asymptotic distribution of the maximum of profile scores, even under weakly dependence conditions. Simulation studies show the proposed method is adequate for moderate sample sizes. The methodology is illustrated with an immunoglobulin protein domain study example.

1 citations


Reference EntryDOI
15 Jul 2005