Efisiensi Asimtotik Penduga Kemungkinan Maksimum dengan Pendekatan Himpunan Kabur  

Oleh:

Dwiatmoko, Ig. Aris

Jenis: Article from Journal - ilmiah nasional - tidak terakreditasi DIKTI
Dalam koleksi: SIGMA: Jurnal Sains dan teknologi vol. 1 no. 1 (Nov. 1997), page 12-26.
Topik: Fuzzy Set; Maximum Likelihood Estimator; Efficiency; Asympotic

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: SS25.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

There is still no unified theory that proves the asymptotic efficiency of maximum likelihood estimator. A classical proof, an example of which is Cramer’s, holds only under the so-called regularity condition. Other conditions have been proposed and are presented here, notably that one by Daniels for non-regular case and by Wolfowitz, which more or less a generalization of Cramer’s, since he assumes also the same regularity conditions although of a broader scope and an additional condition on competing estimator called, the Uniformity Condition. ne new concept that will perhaps lead to a unified proof for the asymptotic efficiency of maximum likelihood estimator without even modifying the same is the concept of ufuzzy sets” Here we consider the uparameter space” generated by the maximum likelihood estimator, as n is varried, as fuzzy and show that finding asymptotic efficiency is equivalent to finding an element of the set whose value of its membership function is a maximum.

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