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Dergiler / Hacettepe Journal of Mathematics and Statistics / 2019 / Cilt: 48 - Sayı: 1

Calibration of the empirical likelihood for semiparametric varying-coe cient partially linear models with diverging number of parameters

Junwei HE
Xia CHEN
Sayfa
230–241
Yayın Tarihi
2022-10-18
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Some simulation studies are conducted to illustrate our approach.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This article is concerned with the calibration of the empirical likelihood for semiparametric varying-coefficient partially linear models with diverging number of parameters.
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Temel Bulgular & Veri:However, there is always substantial lack-of-fit, when the empirical likelihood ratio is calibrated by a bias-corrected empirical likelihood, producing tests with type I errors much larger than nominal levels.
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Sonuç & Katkı:Some simulation studies are conducted to illustrate our approach.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

This article is concerned with the calibration of the empirical likelihood for semiparametric varying-coefficient partially linear models with diverging number of parameters. However, there is always substantial lack-of-fit, when the empirical likelihood ratio is calibrated by a bias-corrected empirical likelihood, producing tests with type I errors much larger than nominal levels. So we consider an eective calibration method and study the asymptotic behavior of this bias-corrected empirical likelihood ratio function. Some simulation studies are conducted to illustrate our approach.

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Bu Makaleye Atıf Yap

HE, J., CHEN, X. (2022). Calibration of the empirical likelihood for semiparametric varying-coe cient partially linear models with diverging number of parameters. Hacettepe Journal of Mathematics and Statistics, Cilt: 48 - Sayı: 1, 230–241. https://ajindex.com/articles/529786

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Kaynakça (16)

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