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| Author: | Stephens, D. |
| Title: | Bayesian retrospective multiple-changepoint identification |
| Journal: | Applied Statistics
1994 : VOL. 43:1, p. 159-178 |
| Index terms: | MODELS BAYESIAN STATISTICS METHODOLOGY |
| Language: | eng |
| Abstract: | Changepoint identification is important in many data analysis problems, such as industrial control and medical diagnosis - given a data sequence, the author wishes to make inference about one or more points of the sequence at which there is a change in the model or parameters driving the system. For long data sequences, however, analysis can become computationally prohibitive, and for complex non-linear models analytical and conventional numerical techniques are infeasible. |
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