Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data
Proceedings of the 2015 International Symposium in Statistics
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Beschreibung
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.
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.
Offers clear differences between structural and longitudinal correlations for the analysis of repeated multivariate data in different setups Uses parametric longitudinal correlation models unlike the existing studies Provides a comprehensive presentation by bringing together spatial-temporal and familial-longitudinal data analysis both for continuous and discrete data Includes supplementary material: sn.pub/extras
Autor*in
Brajendra C. Sutradhar
Themen in »Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data«
Auto-correlation models Longitudinal multinomial data Measurement errors Missing data Parametric longitudinal correlations outliers