Articoli correlati a Nonparametric Methods in Change Point Problems: 243
Sinossi
The explosive development of information science and technology puts in new problems involving statistical data analysis. These problems result from higher re quirements concerning the reliability of statistical decisions, the accuracy of math ematical models and the quality of control in complex systems. A new aspect of statistical analysis has emerged, closely connected with one of the basic questions of cynergetics: how to "compress" large volumes of experimental data in order to extract the most valuable information from data observed. De tection of large "homogeneous" segments of data enables one to identify "hidden" regularities in an object's behavior, to create mathematical models for each seg ment of homogeneity, to choose an appropriate control, etc. Statistical methods dealing with the detection of changes in the characteristics of random processes can be of great use in all these problems. These methods have accompanied the rapid growth in data beginning from the middle of our century. According to a tradition of more than thirty years, we call this sphere of statistical analysis the "theory of change-point detection. " During the last fifteen years, we have witnessed many exciting developments in the theory of change-point detection. New promising directions of research have emerged, and traditional trends have flourished anew. Despite this, most of the results are widely scattered in the literature and few monographs exist. A real need has arisen for up-to-date books which present an account of important current research trends, one of which is the theory of non parametric change--point detection.
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Recensione
`... excellent monograph ... highly recommended ... as a graduate-level textbook on the subject, as well as an outstanding source of information for everyone doing research in these and related areas of random processes and mathematical statistics.'
Mathematical Reviews, 95d
Contenuti
Preface. Introduction: Goals and problems of change point detection. 1. Preliminary considerations. 2. State-of-the-art review. 3. A posteriori change point problems. 4. Sequential change point detection problems. 5. Disorder detection of random fields. 6. Applications of nonparametric change point detection methods. 7. Proofs, new results and technical details. References.
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Nonparametric Methods in Change Point Problems
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The explosive development of information science and technology puts in new problems involving statistical data analysis. These problems result from higher re quirements concerning the reliability of statistical decisions, the accuracy of math ematical models and the quality of control in complex systems. A new aspect of statistical analysis has emerged, closely connected with one of the basic questions of cynergetics: how to 'compress' large volumes of experimental data in order to extract the most valuable information from data observed. De tection of large 'homogeneous' segments of data enables one to identify 'hidden' regularities in an object's behavior, to create mathematical models for each seg ment of homogeneity, to choose an appropriate control, etc. Statistical methods dealing with the detection of changes in the characteristics of random processes can be of great use in all these problems. These methods have accompanied the rapid growth in data beginning from the middle of our century. According to a tradition of more than thirty years, we call this sphere of statistical analysis the 'theory of change-point detection. ' During the last fifteen years, we have witnessed many exciting developments in the theory of change-point detection. New promising directions of research have emerged, and traditional trends have flourished anew. Despite this, most of the results are widely scattered in the literature and few monographs exist. A real need has arisen for up-to-date books which present an account of important current research trends, one of which is the theory of non parametric change--point detection. 222 pp. Englisch. Codice articolo 9780792321224
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The explosive development of information science and technology puts in new problems involving statistical data analysis. These problems result from higher re quirements concerning the reliability of statistical decisions, the accuracy of math ematical models and the quality of control in complex systems. A new aspect of statistical analysis has emerged, closely connected with one of the basic questions of cynergetics: how to 'compress' large volumes of experimental data in order to extract the most valuable information from data observed. De tection of large 'homogeneous' segments of data enables one to identify 'hidden' regularities in an object's behavior, to create mathematical models for each seg ment of homogeneity, to choose an appropriate control, etc. Statistical methods dealing with the detection of changes in the characteristics of random processes can be of great use in all these problems. These methods have accompanied the rapid growth in data beginning from the middle of our century. According to a tradition of more than thirty years, we call this sphere of statistical analysis the 'theory of change-point detection. ' During the last fifteen years, we have witnessed many exciting developments in the theory of change-point detection. New promising directions of research have emerged, and traditional trends have flourished anew. Despite this, most of the results are widely scattered in the literature and few monographs exist. A real need has arisen for up-to-date books which present an account of important current research trends, one of which is the theory of non parametric change--point detection. Codice articolo 9780792321224
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Nonparametric Methods in Change Point Problems
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Springer, Springer Jan 1993, 1993
ISBN 10: 0792321227
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The explosive development of information science and technology puts in new problems involving statistical data analysis. These problems result from higher re quirements concerning the reliability of statistical decisions, the accuracy of math ematical models and the quality of control in complex systems. A new aspect of statistical analysis has emerged, closely connected with one of the basic questions of cynergetics: how to 'compress' large volumes of experimental data in order to extract the most valuable information from data observed. De tection of large 'homogeneous' segments of data enables one to identify 'hidden' regularities in an object's behavior, to create mathematical models for each seg ment of homogeneity, to choose an appropriate control, etc. Statistical methods dealing with the detection of changes in the characteristics of random processes can be of great use in all these problems. These methods have accompanied the rapid growth in data beginning from the middle of our century. According to a tradition of more than thirty years, we call this sphere of statistical analysis the 'theory of change-point detection. ' During the last fifteen years, we have witnessed many exciting developments in the theory of change-point detection. New promising directions of research have emerged, and traditional trends have flourished anew. Despite this, most of the results are widely scattered in the literature and few monographs exist. A real need has arisen for up-to-date books which present an account of important current research trends, one of which is the theory of non parametric change--point detection.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 222 pp. Englisch. Codice articolo 9780792321224
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