Hypothesis Testing and Confidence Intervals for a Multiplicative Poisson Model With Applications to Reliability and Bioassay.
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WISCONSIN UNIV MADISON MATHEMATICS RESEARCH CENTER
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ATIVE INTEGERS AND LET Y sub ij be mutually independent Poisson random variables with parameters n sub ijalpha sub ibeta sub j respectively. N n sub ij is called the design matrix and n sub ij may be regarded as the number of observations on independent Poisson random variables with parameters alpha sub ibeta sub j. Let theta the product from j1 to m of beta sub j. This is a natural parameter of interest in models using increased severity testing in reliability theory and in bioassay problems. When certain conditions on the design matrix are satisfied, tests of hypotheses and confidence intervals for theta are obtained. The randomized forms of these tests and confidence intervals will be uniformly most powerful similar tests and uniformly most accurate unbiased confidence intervals respectively. Author
- Statistics and Probability