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Inference on Classical Change Point Problem

Gaur, Naveen Prakash (2017) Inference on Classical Change Point Problem. Masters thesis, Indian Institute of Science Education and Research Kolkata.

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    Abstract

    Irrespective of being an age old problem, classical change point problem draws the attention of a statistician for its wide applications. The maximum likelihood method is mostly used for detection of a change point in this setup. But it is interesting to note that maximum likelihood method and CUSUM method both give a false alarm of the existence of change point even though there is no change point at all in the given sequence of the data. We have studied mean change problem of Gaussian sequence for a known and an unknown variances. Apart from the maximum likelihood estimator, we use other plug-in estimators of the variance in the estimation and the testing problems related to the change point. We find that the newly proposed testing procedure is at par or even better than the maximum likelihood based testing procedure. Similar results are also observed for multiple change-point problems.

    Item Type: Thesis (Masters)
    Additional Information: Supervisors: Dr. Buddhananda Banerjee (IIT Kharagpur) and Dr. Satyaki Mazumder
    Uncontrolled Keywords: Classical Change Point Problem; Multiple Change Point; Single Change Point
    Subjects: Q Science > QA Mathematics
    Divisions: Department of Mathematics and Statistics
    Depositing User: IISER Kolkata Librarian
    Date Deposited: 07 Nov 2017 15:20
    Last Modified: 08 Nov 2017 13:28
    URI: http://eprints.iiserkol.ac.in/id/eprint/547

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