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Ump (uniform most power) tests and umpu (uniformly most power unbiased) tests in statistical inference. It includes examples of ump tests for uniform distributions and umpu tests for known cumulative distribution functions and negative binomial distributions. The document also explains how to show the non-existence of a ump test and how to obtain a umpu test of a given size.
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TA: Yuan Jiang Email: [email protected]
April 1, 2008
Example 1. Let (X 1 , ..., Xn) be a random sample from the uniform distri- bution on (θ, θ + 1), θ ∈ R. Suppose that n ≥ 2. (i) Show that a UMP test of size α ∈ (0, 1) for testing H 0 : θ ≤ 0 versus H 1 : θ > 0 is of the form
T∗(X(1), X(n)) =
0 X(1) < 1 − α^1 /n, X(n) < 1 1 otherwise,
where X(j) is the jth order statistic. (ii) Does the family of all densities of (X(1), X(n)) have monotone likelihood ratio?
Example 2. Let F and G be two known cumulative distribution functions on R and X be a single observation from the cumulative distribution function θF (x) + (1 − θ)G(x), where θ ∈ [0, 1] is unknown. Consider H 0 : θ ∈ [θ 1 , θ 2 ] versus H 1 : θ 6 ∈ [θ 1 , θ 2 ], where 0 < θ 1 ≤ θ 2 < 1 are constants. (i) Show that a UMP test does not exist. (ii) Obtain a UMPU (uniformly most power unbiased) test of size α.
Example 3. Let X 1 and X 2 be independently distributed as the negative binomial distributions with sizes n 1 and n 2 and probabilities p 1 and p 2 , re- spectively, where ni’s are known and pi’s are unknown. (i) Show that there exists a UMPU test of size α for testing H 0 : p 1 ≤ p 2 versus H 1 : p 1 > p 2. (ii) Let Y = X 1 and U = X 1 + X 2. Determine the conditional distribution of Y given U when n 1 = n 2 = 1.
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