Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Particle swarm optimization based Liu-type estimator
AU - Inan, Deniz
AU - Egrioglu, Erol
AU - Sarica, Busenur
AU - Askin, Oykum Esra
AU - Tez, Mujgan
PY - 2017/11/17
Y1 - 2017/11/17
N2 - In this study, a new method for the estimation of the shrinkage and biasing parameters of Liu-type estimator is proposed. Because k is kept constant and d is optimized in Liu’s method, a (k, d) pair is not guaranteed to be the optimal point in terms of the mean square error of the parameters. The optimum (k, d) pair that minimizes the mean square error, which is a function of the parameters k and d, should be estimated through a simultaneous optimization process rather than through a two-stage process. In this study, by utilizing a different objective function, the parameters k and d are optimized simultaneously with the particle swarm optimization technique.
AB - In this study, a new method for the estimation of the shrinkage and biasing parameters of Liu-type estimator is proposed. Because k is kept constant and d is optimized in Liu’s method, a (k, d) pair is not guaranteed to be the optimal point in terms of the mean square error of the parameters. The optimum (k, d) pair that minimizes the mean square error, which is a function of the parameters k and d, should be estimated through a simultaneous optimization process rather than through a two-stage process. In this study, by utilizing a different objective function, the parameters k and d are optimized simultaneously with the particle swarm optimization technique.
KW - Collinearity
KW - Linear regression
KW - Liu-type estimator
KW - Particle swarm optimization
KW - Ridge regression estimator
U2 - 10.1080/03610926.2016.1267759
DO - 10.1080/03610926.2016.1267759
M3 - Journal article
AN - SCOPUS:85028566027
VL - 46
SP - 11358
EP - 11369
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
SN - 0361-0926
IS - 22
ER -