Bootstrap Methods in a Class of Non - Linear Regression Models
نویسنده
چکیده
Dalam kertas ini, prestasi ralat piawai bootstrap bagi anggaran berpemberat MM (WMM) dibandingkan dengan ralat piawai Monte Carlo dan ralat piawai Berasimptot. Sifat-sifat selang keyakinan bootstrap bagi anggaran berpemberat WMM seperti 'Percentile' (PB), 'Bias-corrected Percentile' (BCP), 'Bias and Accelerated' (BC.), 'Studentzed Percentile' (SPB) dan 'Symmetric' (SB) te1ah diperiksa dan dibandingkan. Keputusan kajian menunjukkan bahawa BSE boleh dianggap hampir kepada ASE dan MCSE sehingga 20% titik terpencil. BC. mempunyai sifat yang menarik dari segi kebarangkalian liputan, kesamaan hujung dan purata panjang selang yang lebih baik jika dibandingkan dengan kaedah lain.
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