Estimating a uniform distribution when data are measured with a normal additive error with unknown variance
作者： Mirta Benšić , Kristian Sabo
DOI: 10.1080/02331880903076645
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摘要: The problem of estimating the width a symmetric uniform distribution on line together with error variance, when data are measured normal additive error, is considered. main purpose to analyse maximum-likelihood (ML) estimator and compare it moment-method estimator. It shown that this two-parameter model regular so ML asymptotically efficient. Necessary sufficient conditions given for existence As numerical problems known frequently occur while computing in model, useful suggestions also given.
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