Displaying similar documents to “Sharper variance upper bound for unbiased estimation in inverse sampling.”

Unbiased estimation for two-parameter exponential distribution under time censored sampling

S. Sengupta (2009)

Applicationes Mathematicae

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The problem considered is that of unbiased estimation for a two-parameter exponential distribution under time censored sampling. We obtain a necessary form of an unbiasedly estimable parametric function and prove that there does not exist any unbiased estimator of the parameters and the mean of the distribution. For reliability estimation at a specified time point, we give a necessary and sufficient condition for the existence of an unbiased estimator and suggest an unbiased estimator...

Estimation of the size of a closed population

S. Sengupta (2010)

Applicationes Mathematicae

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The problem considered is that of estimation of the size (N) of a closed population under three sampling schemes admitting unbiased estimation of N. It is proved that for each of these schemes, the uniformly minimum variance unbiased estimator (UMVUE) of N is inadmissible under square error loss function. For the first scheme, the UMVUE is also the maximum likelihood estimator (MLE) of N. For the second scheme and a special case of the third, it is shown respectively that an MLE and...

Unbiased estimation of reliability for two-parameter exponential distribution under time censored sampling

S. Sengupta (2010)

Applicationes Mathematicae

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The problem considered is that of unbiased estimation of reliability for a two-parameter exponential distribution under time censored sampling. We give necessary and sufficient conditions for the existence of uniformly minimum variance unbiased estimator and also provide a characterization of a complete class of unbiased estimators in situations where unbiased estimators exist.

On the convergence of the Bhattacharyya bounds in the multiparametric case

Abdulghani Alharbi (1994)

Applicationes Mathematicae

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Shanbhag (1972, 1979) showed that the diagonality of the Bhattacharyya matrix characterizes the set of normal, Poisson, binomial, negative binomial, gamma or Meixner hypergeometric distributions. In this note, using Shanbhag's techniques, we show that if a certain generalized version of the Bhattacharyya matrix is diagonal, then the bivariate distribution is either normal, Poisson, binomial, negative binomial, gamma or Meixner hypergeometric. Bartoszewicz (1980) extended the result of...

On some strategies using auxiliary information for estimating finite population mean.

L. N. Sahoo, J. Sahoo, Mariano Ruiz Espejo (1998)

Qüestiió

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This paper presents an empirical investigation of the performance of five strategies for estimating the finite population mean using parameters such as mean or variance or both of an auxiliary variable. The criteria used for the choices of these strategies are bias, efficiency and approach to normality (asymmetry).