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Contributions to the Large Sample Theory of Estimation
Estimation of Several Unknown Parameters
Transformed BetaVariables Moments and Probability
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alternative apply approximation assume asymptotically efficient asymptotically equivalent asymptotically normally B-transforms behaviour best linear estimates Blom bounded c-sequence calculation coefficients gt Condition C1 consider constants converge corresponding defined definition denote derived determined discontinuity point discussed efficient estimate end-points equal error term estimates from Type example exponential distribution expressions follows fr.f function Further given Hence inequality leading term Lemma linear combination location and scale matrix mean value formula method modification nearly best estimates nearly best linear nearly unbiased estimates non-singular normal distribution notation observe order statistics problem proof proved quantities random variable range of variation rectangular distribution relations remainder term remark replaced respect S-corrected sample-size satisfies Condition scale parameters sequence situation Suppose tends to zero theorem in 8.9 tion transformed beta-variables TRB-variables triangular distribution Type 2 distributions unbiased nearly best uniform Type unknown parameters valid variances and covariances