利用加权对称估计量对季节性时间序列的单位根检验(英文)

Unit Root Test with the Weighted Symmetric Estimator for the Seasonal Time Series

本文提出对季节性时间序列利用加权对称估计量的单位根检验，导出相应统计量的极限分布．用ＭｏｎｔｅＣａｒｌｏ方法计算经验百分位数及检验势，并对最小平方估计量，简单对称估计量和加权对称估计量的经验检验势作了比较．

In this thesis, we propose test statistics based on the weighted symmetric estimators for seasonal time series autoregressive models with a unit root and derive. representations for the limit distributions of the estimators and pivotal statistics. The empirical percentiles of the distributions for time series that has a unit root at the seasonal lag are computed for finite samples and limit case by Monte Carlo method. By comparison of the empirical powers, we show that the test statistics with the weighted symmetric estimators are more powerful than that with the ordinary least squares estimators and simple symmetric estimators for the seasonal means model.