A Lower Bound for the Bayes Risk for Testing Sequentially the Sign of the Drift Parameter of a Wiener Process.

Abstract

Let x(t) be a Wiener process with drift micron and variance 1 per unit of time. For testing H: micron less than or equal to 0 was A: micron greater than 0 with the loss function (micron) if the wrong decision is made and 0 otherwise, c cost of observation per unit time and micron has a prior distribution which is normal with mean 0 and variance delta sub 0 to the 2nd power, the authors followed an idea of Bickel and Yahav to obtain a lower bound for the Bayes risk and showed that this lower bound is strict as delta sub 0 approaches limit of infinity for all c. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1983
Accession Number
ADA129231

Entities

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  • Ashim Mallik
  • Yi-ching Yao

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  • Massachusetts Institute of Technology

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  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms