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- W1986394430 abstract "Let#!, . . ., xn deno te s (not necessarily independent) observed values of a random variable f, which is distributed over a space S according to a distribution Pz(x, 0i, . . ., 0S). I t is assumed that Pz(x, 0i, . . ., 0S) is completely specified except for the s unknown parameters 0U . . ., 0S. These parameters may be represented by a point 6=(d1, . . ., 0S) in the s-dimensional Euclidean parameter space 12. Also X—(xi, . . ., xn) is a point in the n-dimensional Euclidean sample space, M. We shall assume that Pz(x, 0) is absolutely continuous, that is, £ possesses an integrable probability density function g^x, 0). Let p(X, 6)=p(x1, . . ., xn, 0) denote the joint probability density function of the observations at XeM. A statistical point estimate of a parameter 0*. which ranges over a subset co* of one-dimensional Euclidean space, is a function ft{X) of the sample values that takes on values in ut. Let Wfi(X), 0] be a nonnegative measurable function denned for all 0e& and XeM. W[fi(X), .0] is a weight function that represents the relative seriousness of taking ft(X) as the value of 0* for any particular sample point X. The function" @default.
- W1986394430 created "2016-06-24" @default.
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- W1986394430 date "1952-01-01" @default.
- W1986394430 modified "2023-09-27" @default.
- W1986394430 title "Uniformly best constant risk and minimax point estimates" @default.
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- W1986394430 doi "https://doi.org/10.6028/jres.048.004" @default.
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