Henderson's method approach to Kernel prediction in partially linear mixed models

Yükleniyor...
Küçük Resim

Tarih

2020

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Sivas Cumhuriyet Üniversitesi Fen Fakültesi

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

In this article, we propose Kernel prediction in partially linear mixed models by usingHenderson's method approach. We derive the Kernel estimator and the Kernel predictor viathe mixed model equations (MMEs) of Henderson's that they give the best linear unbiasedestimation (BLUE) of the fixed effects parameters and the nonparametric functioncomputationally easier and the best linear unbiased prediction (BLUP) of the random effectsparameters as by-products. Additionally, asymptotic property of the Kernel estimator isinvestigated. A Monte Carlo simulation study is supported to illustrate the performance ofKernel prediction in partially linear mixed models and then, we finalize the article with thehelp of conclusion and discussion part to summarize the findings.

Açıklama

Anahtar Kelimeler

Henderson’s method, Kernel estimator, Kernel predictor, Partially linear mixed model, Semiparametric model

Kaynak

Cumhuriyet Science Journal

WoS Q Değeri

Scopus Q Değeri

Cilt

41

Sayı

3

Künye

Kuran, Ö. ve Yalaz, S. (2020). Henderson's method approach to Kernel prediction in partially linear mixed models. Cumhuriyet Science Journal, 41(3), 571-579.