Partially linear multivariate regression in the presence of measurement error
Yükleniyor...
Tarih
2020
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Korean Statistical Society
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this paper, a partially linear multivariate model with error in the explanatory variable of the nonparametric part, and an m dimensional response variable is considered. Using the uniform consistency results found for the estimator of the nonparametric part, we derive an estimator of the parametric part. The dependence of the convergence rates on the errors distributions is examined and demonstrated that proposed estimator is asymptotically normal. In main results, both ordinary and super smooth error distributions are considered. Moreover, the derived estimators are applied to the economic behaviors of consumers. Our method handles contaminated data is founded more effectively than the semiparametric method ignores measurement errors
Açıklama
WOS:000580627300002
Anahtar Kelimeler
Asymptotic normality, Engel curves, Errors in variables, Kernel smoothing, Multivariate regression, Partially linear model
Kaynak
Communications for Statistical Applications and Methods
WoS Q Değeri
N/A
Scopus Q Değeri
Q4
Cilt
27
Sayı
5
Künye
Yalaz, S. ve Tez, M. (2020). Partially linear multivariate regression in the presence of measurement error. Communications for Statistical Applications and Methods, 27(5), 511-521.
