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Synopsis
Decision making in all spheres of activity involves uncertainty. If rational decisions have to be made, they have to be based on the past observations of the phenomenon in question. Data collection, model building and inference from the data collected, validation of the model and refinement of the model are the key steps or building blocks involved in any rational decision making process. Stochastic processes are widely used for model building in the social, physical, engineering, and life sciences as well as in financial economics. Statistical inference for stochastic processes is of great importance from the theoretical as well as from applications point of view in model building. During the past twenty years, there has been a large amount of progress in the study of inferential aspects for continuous as well as discrete time stochastic processes. Diffusion type processes are a large class of continuous time processes which are widely used for stochastic modelling. the book aims to bring together several methods of estimation of parameters involved in such processes when the process is observed continuously over a period of time or when sampled data is available as generally feasible.
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About the Author
Bhagavatula Lakshmi Surya Prakasa Rao is an Indian statistician. He was born on 6 October 1942 in Porumamilla, Andhra Pradesh. He completed his B.A. course in Mathematics from Andhra University in 1960 and moved to the Indian Statistical Institute, Kolkata, where he completed his M.Stat in Statistics in 1962.
Review
Reading the text generates new questions, which is indicative of a generous high quality text. The book will be very useful both for applications and for further development of this important area. -- Biometrics 20010301
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- PublisherWiley
- Publication date2010
- ISBN 10 0470711124
- ISBN 13 9780470711125
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages366
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Hardcover. Condition: new. Hardcover. Decision making in all spheres of activity involves uncertainty. If rational decisions have to be made, they have to be based on the past observations of the phenomenon in question. Data collection, model building and inference from the data collected, validation of the model and refinement of the model are the key steps or building blocks involved in any rational decision making process. Stochastic processes are widely used for model building in the social, physical, engineering, and life sciences as well as in financial economics. Statistical inference for stochastic processes is of great importance from the theoretical as well as from applications point of view in model building. During the past twenty years, there has been a large amount of progress in the study of inferential aspects for continuous as well as discrete time stochastic processes. Diffusion type processes are a large class of continuous time processes which are widely used for stochastic modelling. the book aims to bring together several methods of estimation of parameters involved in such processes when the process is observed continuously over a period of time or when sampled data is available as generally feasible. Decision making in all spheres of activity involves uncertainty. If rational decisions have to be made, they have to be based on the past observations of the phenomenon in question. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780470711125
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