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＜電子ブック＞
Growth Curve and Structural Equation Modeling : Topics from the Indian Statistical Institute / edited by Ratan Dasgupta
(Springer Proceedings in Mathematics & Statistics. ISSN:21941017 ; 132)

版	1st ed. 2015.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2015
本文言語	英語
大きさ	XII, 299 p. 169 illus., 98 illus. in color : online resource
著者標目	Dasgupta, Ratan editor SpringerLink (Online service)
件　名	LCSH:Biometry LCSH:Statistics  FREE:Biostatistics FREE:Statistical Theory and Methods FREE:Statistics
一般注記	Plant Sensitivity and Growth Curve Analysis of Elephant Foot Yam.-  Some remarks on pseudo panel data -- Rates of convergence in CLT for two sample U-statistics in non iid case and multiphasic growth curve -- Estimation of animal abundance through imperfectly characterizing signatures -- Growth Curve of Elephant Foot Yam, One sided Estimation and Confidence Band -- Interrelationship between Economic Growth and Income Inequality: The Indian Experience -- Growth Curve reconstruction in Damaged Experiment via Nonlinear Calibration -- Growth Curve of Phase change in presence of Polycystic Ovary Syndrome -- Declining patterns of average height of adult Indians between 20-49 years: State wise trends and influence of socioeconomic factors -- Growth Model of some Vernacular Word Usage during Political Transition -- Some Further Results on Nonuniform Rates of Convergence to Normality in Finite Population with applications -- Unbounded Growth Model for Word Frequencies in Political Transition -- A Statistical Analysis of micro RNA: classification, identification and conservation based on structure and function -- Longitudinal Growth of Elephant Foot Yam and Some Characterization Theorems- Optimal Choice of Small Regular Shapes for Accidentally Damaged Tessellation This book describes some recent trends in GCM research on different subject areas, both theoretical and applied. This includes tools and possibilities for further work through new techniques and modification of existing ones. A growth curve is an empirical model of the evolution of a quantity over time. Growth curves in longitudinal studies are used in disciplines including biology, statistics, population studies, economics, biological sciences, sociology, nano-biotechnology, and fluid mechanics. The volume includes original studies, theoretical findings and case studies from a wide range of applied work. This volume builds on presentations from a GCM workshop held at the Indian Statistical Institute, Giridih, January 18-19, 2014. This book follows the volume Advances in Growth Curve Models, published by Springer in 2013. The results have meaningful application in health care, prediction of crop yield, child nutrition, poverty measurements, estimation of growth rate, and other research areas HTTP:URL=https://doi.org/10.1007/978-3-319-17329-0

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