EFFICIENT TWO-PARAMETER ESTIMATOR IN LINEAR REGRESSION MODEL

Publications

Share / Export Citation / Email / Print / Text size:

Statistics in Transition New Series

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics , Statistics & Probability

GET ALERTS

ISSN: 1234-7655
eISSN: 2450-0291

DESCRIPTION

21
Reader(s)
55
Visit(s)
0
Comment(s)
0
Share(s)

SEARCH WITHIN CONTENT

FIND ARTICLE

Volume / Issue / page

Related articles

VOLUME 20 , ISSUE 2 (June 2019) > List of articles

EFFICIENT TWO-PARAMETER ESTIMATOR IN LINEAR REGRESSION MODEL

Ashok V. Dorugade

Keywords : multicollinearity, ridge regression, two-parameter estimator, mean squared error

Citation Information : Statistics in Transition New Series. Volume 20, Issue 2, Pages 173-185, DOI: https://doi.org/10.21307/stattrans-2019-021

License : (CC BY-NC-ND 4.0)

Published Online: 22-July-2019

ARTICLE

ABSTRACT

In this article, two-parameter estimators in linear model with multicollinearity are considered. An alternative efficient two-parameter estimator is proposed and its properties are examined. Furthermore, this was compared with the ordinary least squares (OLS) estimator and ordinary ridge regression (ORR) estimators. Also, using the mean squares error criterion the proposed estimator performs more efficiently than OLS estimator, ORR estimator and other reviewed two-parameter estimators. A numerical example and simulation study are finally conducted to illustrate the superiority of the proposed estimator.

Content not available PDF Share

FIGURES & TABLES

REFERENCES

AKDENIZ, F., KACIRANLAR, S., (1995). On the almost unbiased generalized Liu estimator and unbiased estimation of the bias and MSE, Commun. Statist. Theor. Meth., 24, pp. 1789–1797.

CROUSE, R. H., JIN, C., HANUMARA, R. C., (1995). Unbiased ridge estimation with prior information and ridge trace, Commun. Statist. Theor. Meth., 24, pp. 2341–2354.

DORUGADE, A. V., (2014). Modified Two Parameter Estimator in Linear regression, Statistics in Transition - new series, 15 (1), pp. 23–36.

GRUBER, M. H. J., (1998). Improving efficiency by shrinkage the James–Stein and Ridge regression estimators. Marcell Dekker, NewYork. 

HOERL, A. E., (1962). Application of ridge analysis to regression problems, Chemical Engineering Progress., 68, pp. 54–59.

HOERL, A. E., KENNARD, R. W., (1968). On regression analysis and biased estimation, Technometrics, 10, pp. 422–423. 

HOERL, A. E., KENNARD, R. W., (1970a). Ridge regression: Biased estimation for non orthogonal problems, Technometrics, 12, pp. 55–67.

HOERL, A. E., KENNARD, R. W., (1970b). Ridge regression: Applications to Nonorthogonal problems, Technometrics, 12, pp. 69–82.

HOERL, A. E., KENNARD, R. W., BALDWIN, K. F., (1975). Ridge regression:

Some Simulations, Commun. Statist., 4, pp. 105–123.

KACIRANLAR, S., SAKALLIOGLU, S., AKDENIZ, F., STYAN, G. P. H., WERNER, H. J., (1999). A new biased estimator in linear regression and a detailed analysis of the widely-analysed dataset on Portland Cement, Sankhya Ind. J. Statist., 61, pp. 443–459.

LIU, K., (1993). A new class of biased estimate in linear regression, Commun. Statist. Theor. Meth., 22, pp. 393–402.

LIU, K., (2003). Using Liu-type estimator to combat Collinearity. Commun, Statist. Theor. Meth., 32, pp. 1009–1020.

MCDONALD G. C., GALARNEAU, D. I., (1975).  A Monte Carlo evaluation of some ridge-type estimators, J Am Stat Assoc., 20, pp. 407–416.

MONTGOMERY, D. C., PECK, E. A., VINING, G. G., (2006). Introduction to linear  regression analysis. John Wiley and Sons, New York.

OZKALE, M. R., KACIRANLAR , S., (2007). The restricted and unrestricted twoparameter estimators, Commun. Statist. Theor. Meth., 36, pp. 2707–2725.

SINGH, B., CHAUBEY, Y. P., (1987). On some improved ridge estimators, Stat Papers, 28, pp. 53–67.

YANG, H., CHANG, X., (2010). A New Two-Parameter Estimator in Linear Regression, Commun. Statist. Theor. Meth., 39, pp. 923–934.

WU, J., YANG, H., (2011). Efficiency of an almost unbiased two-parameter estimator in linear regression model, Statistics., 47 (3), pp. 535–545. 

EXTRA FILES

COMMENTS