Statistical inference from stochastic processes : proceedings of the AMS-IMS-SIAM Joint Summer Research Conference held August 9-15, 1987, with support from the National Science Foundation and the Army Research Office

This volume comprises the proceedings of the AMS-IMS-SIAM Summer Research Conference on Statistical Inference from Stochastic Processes, held at Cornell University in August 1987. The conference brought together probabilists and statisticians who have developed important areas of application and mad...

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Main Authors: Prabhu, N. U. (Narahari Umanath), American Mathematical Society, Institute of Mathematical Statistics, Society for Industrial and Applied Mathematics, AMS-IMS-SIAM Joint Summer Research Conference in the Mathematical Sciences on Statistical Inference from Stochastic Processes
Format: eBook Book
Language:English
Published: Providence, R.I American Mathematical Society 1988
Series:Contemporary mathematics
Subjects:
ISBN:9780821850879, 0821850873
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Abstract This volume comprises the proceedings of the AMS-IMS-SIAM Summer Research Conference on Statistical Inference from Stochastic Processes, held at Cornell University in August 1987. The conference brought together probabilists and statisticians who have developed important areas of application and made major contributions to the foundations of the subject. Statistical inference from stochastic processes has been important in a number of areas. For example, in applied probability, major advances have been made in recent years in stochastic models arising in science and engineering. However, the emphasis has been on the formulation and analysis of models rather than on the statistical methodology for hypothesis testing and inference. For these models to be of practical use, procedures for their statistical analysis are essential. In the area of probability models, initial work in inference focused on Markov chains, but many models have given rise to non-Markovian and point processes.In recent years, research in statistical inference from such processes not only solved specific problems but also resulted in major contributions to the conceptual framework of the subject as well as the associated techniques. The objective of the conference was to provide the opportunity to survey and evaluate the current state of the art in this area and to discuss future directions. The papers presented covered five topics within the broad domain of inference from stochastic processes: foundations, counting processes and survival analysis, likelihood and its ramifications, applications to statistics and probability models, and processes in economics. Requiring a graduate level background in probability and statistical inference, this book will provide students and researchers with a familiarity with the foundations of inference from stochastic processes and a knowledge of the current developments in this area.
AbstractList This volume comprises the proceedings of the AMS-IMS-SIAM Summer Research Conference on Statistical Inference from Stochastic Processes, held at Cornell University in August 1987. The conference brought together probabilists and statisticians who have developed important areas of application and made major contributions to the foundations of the subject. Statistical inference from stochastic processes has been important in a number of areas. For example, in applied probability, major advances have been made in recent years in stochastic models arising in science and engineering. However, the emphasis has been on the formulation and analysis of models rather than on the statistical methodology for hypothesis testing and inference. For these models to be of practical use, procedures for their statistical analysis are essential. In the area of probability models, initial work in inference focused on Markov chains, but many models have given rise to non-Markovian and point processes.In recent years, research in statistical inference from such processes not only solved specific problems but also resulted in major contributions to the conceptual framework of the subject as well as the associated techniques. The objective of the conference was to provide the opportunity to survey and evaluate the current state of the art in this area and to discuss future directions. The papers presented covered five topics within the broad domain of inference from stochastic processes: foundations, counting processes and survival analysis, likelihood and its ramifications, applications to statistics and probability models, and processes in economics. Requiring a graduate level background in probability and statistical inference, this book will provide students and researchers with a familiarity with the foundations of inference from stochastic processes and a knowledge of the current developments in this area.
Author American Mathematical Society
AMS-IMS-SIAM Joint Summer Research Conference in the Mathematical Sciences on Statistical Inference from Stochastic Processes
Society for Industrial and Applied Mathematics
Institute of Mathematical Statistics
Prabhu, N. U. (Narahari Umanath)
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Notes "AMS-IMS-SIAM Joint Summer Research Conference in the Mathematical Sciences on Statistical Inference from Stochastic Processes was held at Cornell University, Ithaca, New York" -- T.p. verso
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Snippet This volume comprises the proceedings of the AMS-IMS-SIAM Summer Research Conference on Statistical Inference from Stochastic Processes, held at Cornell...
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SubjectTerms Elliptic operators -- Congresses
Foliations (Mathematics) -- Congresses
Index theory (Mathematics) -- Congresses
Mathematical statistics
Mathematical statistics -- Congresses
Operator algebras -- Congresses
Stochastic processes
Stochastic processes -- Congresses
Title Statistical inference from stochastic processes : proceedings of the AMS-IMS-SIAM Joint Summer Research Conference held August 9-15, 1987, with support from the National Science Foundation and the Army Research Office
URI https://cir.nii.ac.jp/crid/1130282271445670144
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