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Advances in Growth Curve Models: Topics from the Indian Statistical Institute is developed from the Indian Statistical Institute's A National Conference on Growth Curve Models. This conference took place between March 28-30, 2012 in Giridih, Jharkhand, India. Jharkhand is a tribal area. Advances in Growth Curve Models: Topics from the Indian Statistical Institute shares the work of researchers in growth models used in multiple fields. A growth curve is an empirical model of the evolution of a quantity over time. Case studies and theoretical findings, important applications in everything from health care to population projection, form the basis of this volume. Growth curves in longitudinal studies are widely used in many disciplines including: Biology, Population studies, Economics, Biological Sciences, SQC, Sociology, Nano-biotechnology, and Fluid mechanics. Some included reports are research topics that have just been developed, whereas others present advances in existing literature. Both included tools and techniques will assist students and researchers in their future work. Also included is a discussion of future applications of growth curve models.
List of contents
Yam Growth Experiment and Above-ground Biomass as Possible Predictor.- Some Statistical Perspectives of Growth Models in Health Care Plans.- Testing of Growth Curves with Cubic Smoothing Splines.- Non uniform Rates of Convergence to Normality for Two sample U-statistics in Non IID Case with Applications.- Correlated Bivariate Linear Growth Models: Optimal Designs for Slope Parameter Estimation.- Optimal-Time Harvest of Elephant Foot Yam and Related Theoretical Issues.- Evolution of Scour and velocity fluctuation due to turbulence around cylinders.- South Pole Ozone Profile and Lower Tolerance Limit.- Population Distribution of Human Growth Curve Parameters Through a Combination of Longitudinal and Cross-sectional Data.- Tuber Crop Growth and Pareto Model.- Effect of past demographic events on the mtDNA mismatch distribution among the Adi tribe of Arunachal Pradesh, India.- Growth Curve Model in Relation to Extremal Processes based on Stationary Random Variables.- A Method of Population Projection by Using Leslie Matrix in Indian Context.- Indian Statistical Institute and Tata Motors Pune: Growth curve for cumulative defects.- Growth and Nutritional Status of Pre-school Children: A Comparative Study of Jharkhand, Bihar and West Bengal.
About the author
Ratan Dasgupta was born on 15 September 1953 to Manoranjan and Saraswati at Agartala, Tripura. After completion of high school and graduation (1972) at hometown Agartala, he completed his Masters (1975) and Ph.D (1981) degree in Statistics at Indian Statistical Institute, Kolkata; where he is employed as a Professor. Apart from Ph.D topic on rates of convergence in CLT, his areas of research interest are: application of Statistics in Quality Control, fluid mechanics, environment, physics etc. He has published about 60 research papers. He is married to Soma and has a son Debkumar.
Summary
Advances in Growth Curve Models: Topics from the Indian Statistical Institute is developed from the Indian Statistical Institute's A National Conference on Growth Curve Models. This conference took place between March 28-30, 2012 in Giridih, Jharkhand, India. Jharkhand is a tribal area. Advances in Growth Curve Models: Topics from the Indian Statistical Institute shares the work of researchers in growth models used in multiple fields. A growth curve is an empirical model of the evolution of a quantity over time. Case studies and theoretical findings, important applications in everything from health care to population projection, form the basis of this volume. Growth curves in longitudinal studies are widely used in many disciplines including: Biology, Population studies, Economics, Biological Sciences, SQC, Sociology, Nano-biotechnology, and Fluid mechanics. Some included reports are research topics that have just been developed, whereas others present advances in existing literature. Both included tools and techniques will assist students and researchers in their future work. Also included is a discussion of future applications of growth curve models.
