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Advances And Challenges In Parametric And Semiparametric Analysis For Correlated Data Proceedings Of The 2015 International Symposium In Statistics 1st Edition Brajendra C Sutradhar Eds

  • SKU: BELL-5484216
Advances And Challenges In Parametric And Semiparametric Analysis For Correlated Data Proceedings Of The 2015 International Symposium In Statistics 1st Edition Brajendra C Sutradhar Eds
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Advances And Challenges In Parametric And Semiparametric Analysis For Correlated Data Proceedings Of The 2015 International Symposium In Statistics 1st Edition Brajendra C Sutradhar Eds instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 10.64 MB
Pages: 267
Author: Brajendra C. Sutradhar (eds.)
ISBN: 9783319312583, 9783319312606, 3319312588, 331931260X
Language: English
Year: 2016
Edition: 1

Product desciption

Advances And Challenges In Parametric And Semiparametric Analysis For Correlated Data Proceedings Of The 2015 International Symposium In Statistics 1st Edition Brajendra C Sutradhar Eds by Brajendra C. Sutradhar (eds.) 9783319312583, 9783319312606, 3319312588, 331931260X instant download after payment.

This proceedings volume contains eight selected papers that were presented in the International Symposium in Statistics (ISS) 2015 On Advances in Parametric and Semi-parametric Analysis of Multivariate, Time Series, Spatial-temporal, and Familial-longitudinal Data, held in St. John’s, Canada from July 6 to 8, 2015. The main objective of the ISS-2015 was the discussion on advances and challenges in parametric and semi-parametric analysis for correlated data in both continuous and discrete setups. Thus, as a reflection of the theme of the symposium, the eight papers of this proceedings volume are presented in four parts. Part I is comprised of papers examining Elliptical t Distribution Theory. In Part II, the papers cover spatial and temporal data analysis. Part III is focused on longitudinal multinomial models in parametric and semi-parametric setups. Finally Part IV concludes with a paper on the inferences for longitudinal data subject to a challenge of important covariates selection from a set of large number of covariates available for the individuals in the study.

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