TY - JOUR
T1 - Diagnostics in elliptical regression models with stochastic restrictions applied to econometrics
AU - Leiva, Víctor
AU - Liu, Shuangzhe
AU - Shi, Lei
AU - Cysneiros, Francisco José A.
N1 - Publisher Copyright:
© 2015 Taylor & Francis.
PY - 2016/3/11
Y1 - 2016/3/11
N2 - We propose an influence diagnostic methodology for linear regression models with stochastic restrictions and errors following elliptically contoured distributions. We study how a perturbation may impact on the mixed estimation procedure of parameters in the model. Normal curvatures and slopes for assessing influence under usual schemes are derived, including perturbations of case-weight, response variable, and explanatory variable. Simulations are conducted to evaluate the performance of the proposed methodology. An example with real-world economy data is presented as an illustration.
AB - We propose an influence diagnostic methodology for linear regression models with stochastic restrictions and errors following elliptically contoured distributions. We study how a perturbation may impact on the mixed estimation procedure of parameters in the model. Normal curvatures and slopes for assessing influence under usual schemes are derived, including perturbations of case-weight, response variable, and explanatory variable. Simulations are conducted to evaluate the performance of the proposed methodology. An example with real-world economy data is presented as an illustration.
KW - computational statistics
KW - elliptically contoured distributions
KW - generalized least squares
KW - local influence method
KW - maximum-likelihood method
KW - mixed estimation
UR - http://www.scopus.com/inward/record.url?scp=84955205911&partnerID=8YFLogxK
U2 - 10.1080/02664763.2015.1072140
DO - 10.1080/02664763.2015.1072140
M3 - Article
AN - SCOPUS:84955205911
SN - 0266-4763
VL - 43
SP - 627
EP - 642
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
IS - 4
ER -