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Change–point problems arise in a variety of experimental and mathematical sciences, as well as in engineering and health sciences. This rigorously researched text provides a comprehensive review of recent probabilistic methods for detecting various types of possible changes in the distribution of chronologically ordered observations. Further developing the already well–established theory of weighted approximations and weak convergence, the authors provide a thorough survey of parametric and non–parametric methods, regression and time series models together with sequential methods. All but the most basic models are carefully developed with detailed proofs, and illustrated by using a number of data sets. Contains a thorough survey of:
- The Likelihood Approach
- Non–Parametric Methods
- Linear Models
- Dependent Observations
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The Likelihood Approach.
Nonparametric Methods.
Linear Models.
Dependent Observations.
Appendix.
References.
Indexes.
Nonparametric Methods.
Linear Models.
Dependent Observations.
Appendix.
References.
Indexes.
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Miklós Csörgö
Lajos Horváth
Lajos Horváth
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