Classical linear regression model;
Modified maximum likelihood estimation;
Non-normality;
OLS estimator;
AUTOREGRESSIVE MODELS;
ESTIMATING PARAMETERS;
ASYMPTOTIC PROPERTIES;
NONNORMAL REGRESSION;
STRONG CONSISTENCY;
ALTERNATIVE TESTS;
INDEPENDENCE;
HYPOTHESIS;
ERROR;
ESTIMATORS;
D O I:
暂无
中图分类号:
S [农业科学];
学科分类号:
09 ;
摘要:
Regression models form the core of the discipline of econometrics. One of the basic assumptions of classical linear regression model is that the values of the explanatory variables are fixed in repeated sampling. However, in most of the real life cases, particularly in economics the assumption of fixed regressors is not always tenable. Under a non-experimental or uncontrolled environment, the dependent variable is often under the influence of explanatory variables that are stochastic in nature. There is a huge literature related to stochastic regressors in various aspects. In this paper, a historical perspective on some of the works related to stochastic regressor is being tried to pen down based on literature search.
机构:
City Univ Hong Kong, Dept Management Sci, Hong Kong, Hong Kong, Peoples R ChinaCity Univ Hong Kong, Dept Management Sci, Hong Kong, Hong Kong, Peoples R China
Xia, Tian
Wang, Xue-Ren
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h-index: 0
机构:
Yunnan Univ, Dept Stat, Kunming 650091, Peoples R ChinaCity Univ Hong Kong, Dept Management Sci, Hong Kong, Hong Kong, Peoples R China
Wang, Xue-Ren
Jiang, Xue-Jun
论文数: 0引用数: 0
h-index: 0
机构:
Zhongnan Univ Econ & Law, Sch Stat & Math, Wuhan, Peoples R ChinaCity Univ Hong Kong, Dept Management Sci, Hong Kong, Hong Kong, Peoples R China
机构:
Louisiana State Univ, Dept Math, Baton Rouge, LA 70803 USA
Louisiana State Univ, Ctr Computat & Technol, Baton Rouge, LA 70803 USALouisiana State Univ, Dept Math, Baton Rouge, LA 70803 USA