Parameter Estimation of Varying Coefficients Structural EV Model with Time Series

In this paper, the parameters of a p-dimensional linear structural EV （error-in-variable）model are estimated when the coefficients vary with a real variable and the model error is time series.The adjust weighted least squares （AWLS） method is used to estimate the parameters. It is shown thatthe esti...

Full description

Saved in:
Bibliographic Details
Published in:Acta mathematica Sinica. English series 2017-05, Vol.33 (5), p.607-619
Main Authors: Su, Yan Yun, Cui, Heng Jian, Li, Kai Can
Format: Article
Language:English
Subjects:
adjust
asymptotic
Asymptotic methods
Asymptotic properties
coefficient
consistency
Convergence
Estimating techniques
estimators
least
Least squares method
linear
Mathematical models
Mathematics
Mathematics and Statistics
normality
Optimization
Parameter estimation
Parameters
Random variables
Regression analysis
series
squares
stationarytime
Studies
Time series
Varying
weighted
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, the parameters of a p-dimensional linear structural EV （error-in-variable）model are estimated when the coefficients vary with a real variable and the model error is time series.The adjust weighted least squares （AWLS） method is used to estimate the parameters. It is shown thatthe estimators are weakly consistent and asymptotically normal, and the optimal convergence rate isalso obtained. Simulations study are undertaken to illustrate our AWLSEs have good performance.
ISSN:1439-8516
1439-7617
DOI:10.1007/s10114-016-3187-6