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Autor
Chandra Shalini (Banasthali Vidyapit, India), Tyagi Gargi (Banasthali Vidyapit, India)
Tytuł
On the Performance of Some Biased Estimators in a Misspecified Model with Correlated Regressors
Źródło
Statistics in Transition, 2017, vol. 18, nr 1, s. 27-52, wykr., tab., , bibliogr. s. 51-52
Słowa kluczowe
Dobór zmiennych, Estymatory, Regresja liniowa
Variables selection, Estimators, Linear regression
Uwagi
summ.
Abstrakt
In this paper, the effect of misspecification due to omission of relevant variables on the dominance of the r -(k,d) class estimator proposed by Özkale (2012), over the ordinary least squares (OLS) estimator and some other competing estimators when some of the regressors in the linear regression model are correlated, have been studied with respect to the mean squared error criterion. A simulation study and numerical example have been demostrated to compare the performance of the estimators for some selected values of the parameters involved. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Pełny tekst
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Bibliografia
Pokaż
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  9. KAÇIRANLAR, S., SAKALLIOGLU, S., (2001). Combining the Liu estimator and the principal component regression estimator. Communications in Statistics - Theory and Methods, 30, pp. 2699- 2705.
  10. KADIYALA, K., (1986). Mixed regression estimator under misspecification. Economic Letters, 21, pp. 27- 30.
  11. KIBRIA, B., (2003). Performance of some new ridge regression estimators. Communications in Statistics - Theory and Methods, 32, pp. 419-435.
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  16. ÖZKALE, M. R., KAęiRANLAR, S., (2007). The restricted and unrestricted two parameter estimators. Communications in Statistics- Theory and Methods, 36, pp.2707-2725.
  17. ÖZKALE, M. R., (2012). Combining the unrestricted estimators into a single estimator and a simulation study on the unrestricted estimators. Journal of Statistical Computation and Simulation, 82, pp. 653-688.
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ISSN
1234-7655
Język
eng
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