+91-674-249-4082

Submitted by sde on 23 April, 2018 - 22:35

Date/Time:

Wednesday, April 25, 2018 - 11:00 to 12:00

Venue:

SMS seminar Room

Speaker:

Ramprasad Kale

Affiliation:

NISER, 4th year integrated M.Sc student

Title:

Sequential Hypothesis Testing

For simple versus simple hypothesis testing, the famous Neyman-Pearson lemma (1933) provides the best fixed sample size test procedure that has minimum type II error among all the tests that control type I error at some prescribed level. However, it is well-known that even such a best test cannot guarantee control of type II error while retaining the type I error control as long as the sample size is fixed. Abraham Wald (1943) extended the Neyman-Pearson lemma for sequentially observed data by introducing the Sequential Probability Ratio Test (SPRT) that simultaneously controls type I and type II error probabilities at some prefixed levels. In this talk, I will be discussing this test procedure along with boundary conditions, average sample size, the optimality property of SPRT and truncated SPRT. If time permits, I will discuss how to extend this idea for testing k (>2) simple-vs-simple hypotheses with the goal of selecting the correct hypothesis. This problem is known as Multi-hypothesis sequential probability ratio test (MSPRT).

**School of Mathematical Sciences**

NISER, PO- Bhimpur-Padanpur, Via- Jatni, District- Khurda, Odisha, India, PIN- 752050

Tel: +91-674-249-4081

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