A comparison study on regression with stationary nonparametric autoregressive errors

정상 비모수 자기상관 오차항을 갖는 회귀분석에 대한 비교 연구

Yu, Kyusang

  • Received : 2015.12.15
  • Accepted : 2015.12.31
  • Published : 2016.02.29


We compare four methods to estimate a regression coefficient under linear regression models with serially correlated errors. We assume that regression errors are generated with nonlinear autoregressive models. The four methods are: ordinary least square estimator, general least square estimator, parametric regression error correction method, and nonparametric regression error correction method. We also discuss some properties of nonlinear autoregressive models by presenting numerical studies with typical examples. Our numerical study suggests that no method dominates; however, the nonparametric regression error correction method works quite well.


nonparametric autoregressive model;regression;efficiency


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Supported by : 건국대학교