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Advances in multivariate statistical methods [[electronic resource] /] / editor, Ashis SenGupta



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Titolo: Advances in multivariate statistical methods [[electronic resource] /] / editor, Ashis SenGupta Visualizza cluster
Pubblicazione: New Jersey, : World Scientific, c2009
Descrizione fisica: 1 online resource (492 p.)
Disciplina: 519.5/35
Soggetto topico: Multivariate analysis
Statistics
Soggetto genere / forma: Electronic books.
Altri autori: SenguptaA (Ashis)  
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: Foreword; Preface; Contents; 1. High-Dimensional Discrete Statistical Models: UIP, MCP and CSI in Perspectives P. K. Sen; 2. A Review of Multivariate Theory for High Dimensional Data with Fewer Observations M. S. Srivastava; 3. Model Based Penalized Clustering for Multivariate Data S. Ghosh and D. K. Dey; 4. Jacobians Under Constraints and Statistical Bioinformatics K. V. Mardia; 5. Cluster Validation for Microarray Data: An Appraisal V. Pihur, G. N. Brock and S. Datta; 6. Flexible Bivariate Circular Models B. C. Arnold and A. SenGupta
7. Optimal Text Space Representation of Student Essays Using Latent Semantic Analysis A. Villacorta and S. R. Jammalamadaka8. Linear Regression for Random Measures M. M. Rao; 9. Mixed Multivariate Models for Random Sums and Maxima T. J. Kozubowski, A. K. Panorska and F. Biondi; 10. Estimation of the Multivariate Box-Cox Transformation Parameters M. Rahman and L. M. Pearson; 11. Generation of Multivariate Densities R. N. Rattihalli and A. N. Basugade; 12. Smooth Estimation of Multivariate Distribution and Density Functions Y. P. Chaubey
13. Estimation Using Quantile Function Structure with Emphasis on Weibull Distribution G. D. Kollia, G. S. Mudholkar and D. K. Srivastava14. On Optimal Estimating Functions in the Presence of Nuisance Parameters P. Mukhopadhyay; 15. Inference in Exponential Family Regression Models Under Certain Shape Constraints M. Banerjee; 16. Study of Optimal Adaptive Rule in Testing Problem S. K. Bhandari, R. Dutta and R. G. Niyogi; 17. The G-IG Analogies and Robust Tests for Inverse Gaussian Scale Parameters G. S. Mudholkar, H. Wang and R. Natarajan
18. Clusterwise Regression Using Dirichlet Mixtures C. Kang and S. Ghosal19. Bayesian Analysis of Rank Data Using SIR A. K. Laha and S. Dongaonkar; 20. Bayesian Tests of Equality of Stratified Proportions for a Multiple Response Categorical Variable B. Nandram; 21. Respondent-Generated Intervals in Sample Surveys: A Summary S. J. Press and J. M. Tanur; 22. Quality Index and Mahalanobis D2 Statistic R. Dasgupta; 23. AQL Based Multiattribute Sampling Scheme A. Majumdar
24. Multivariate Quality Management in Terms of a Desirability Measure and a Related Result on Purchase Decision: A Distributional Study D. Roy25. Time Series of Categorical Data Using Auto-Mutual Information with Application of Fitting an AR(2) Model A. Biswas and A. Guha; 26. Estimation of Integrated Covolatility for Asynchronous Assets in the Presence of Microstructure Noise R. Sen and Q. Xu; 27. Improving the Hansen-Hurwitz Estimator in PPSWR Sampling A. K. Adhikary
Sommario/riassunto: This volume contains a collection of research articles on multivariate statistical methods, encompassing both theoretical advances and emerging applications in a variety of scientific disciplines. It serves as a tribute to Professor S N Roy, an eminent statistician who has made seminal contributions to the area of multivariate statistical methods, on his birth centenary. In the area of emerging applications, the topics include bioinformatics, categorical data and clinical trials, econometrics, longitudinal data analysis, microarray data analysis, sample surveys, statistical process control, et
Titolo autorizzato: Advances in multivariate statistical methods  Visualizza cluster
ISBN: 1-282-44321-6
9786612443213
981-283-824-4
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910456864003321
Lo trovi qui: Univ. Federico II
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Serie: Statistical science and interdisciplinary research ; ; v. 4.