Detecting influential observations in Liu and modified Liu estimators
Küçük Resim Yok
Tarih
2013
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
TAYLOR & FRANCIS LTD
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In regression, detecting anomalous observations is a significant step for model-building process. Various influence measures based on different motivational arguments are designed to measure the influence of observations through different aspects of various regression models. The presence of influential observations in the data is complicated by the existence of multicollinearity. The purpose of this paper is to assess the influence of observations in the Liu [9] and modified Liu [15] estimators by using the method of approximate case deletion formulas suggested by Walker and Birch [14]. A numerical example using a real data set used by Longley [10] and a Monte Carlo simulation are given to illustrate the theoretical results.
Açıklama
Anahtar Kelimeler
influential observations, diagnostics, multicollinearity, Liu estimator, modified Liu estimator
Kaynak
JOURNAL OF APPLIED STATISTICS
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
40
Sayı
8
