Libri di Obaid Al-Saidy - libri Statistica & Applicazioni

Obaid Al-Saidy

Obaid Al-Saidy
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Vita e Pensiero
Obaid Al-Saidy è professore presso la Sultan Qaboos University nel dipartimento di Statistica e di Matematica.
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Estimation of  = P(X>Y) using ranked set sampling
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digital
format: Article | STATISTICA & APPLICAZIONI - 2010 - 2
Year: 2010
SUMMARY Nonparametric-type estimation of  ¼ PðX > YÞ, based on ranked set sampling (RSS) technique with concomitant random variable, is considered. The maximum likelihood estimation (MLE) of  is also considered using RSS and median ranked set sampling (MRSS) techniques with concomitant random variable. The estimators obtained are compared to their counterparts based on simple random sampling (SRS) using bias and mean square error (MSE). It appears that the suggested nonparametric estimator based on RSS is more efficient than that based on SRS and the MLE based on MRSS is more efficient than the MLE based on RSS which is in turn more efficient than the MLE based on SRS. Keywords: Simple Random Sampling, Ranked Set Sampling, Median Ranked Set Sampling, Nonparametric Estimation; Maximum Likelihood Estimation, Mean Square Error. RIASSUNTO La stima non parametrica di  ¼ PðX > YÞ basata sulla tecnica del Ranked Set Sampling (RSS) con variabile concomitante e` considerata preliminarmente. Successivamente viene trattata la Stima di Massima Verosimiglianza (MLE) di  nel caso Normale usando sia RSS sia il Median Ranked Set Sampling (MRSS) con variabile concomitante. Gli stimatori ottenuti sono confrontati con quelli basati sul Simple Random Sample (SRS) usando il bias e l’errore quadratico medio (MSE). Emerge che lo stimatore non parametrico proposto basato su RSS e`piu` efficiente di quello basato su SRS e lo stimatore MLE basato su MRSS e`piu` efficiente di quello MLE basato su RSS che a sua volta risulta piu` efficiente di quello MLE basato su SRS.
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