TY - JOUR
T1 - Diagnostics in elliptical regression models with stochastic restrictions applied to econometrics
AU - Leiva, Victor
AU - LIU, Shuangzhe
AU - Shi, Lei
AU - Cysneiros, Francisco
N1 - Funding Information:
The research of F.J.A. Cysneiros and V. Leiva was supported by FONDECYT [1120879] (Chile) and Capes, CNPq and FACEPE (Brazil) grants. The research of L. Shi was supported by Natural Science Foundation [grant number 11161053] (China).
Publisher Copyright:
© 2015 Taylor & Francis.
Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2016
Y1 - 2016
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
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
SN - 0266-4763
VL - 43
SP - 627
EP - 642
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
IS - 4
ER -