The paper proposes a statistic to test stationarity of series with κ-stable innovations and structural breaks,obtains the asymptotical distribution of the statistic,and proves the consistency of the test.To obtain cr...The paper proposes a statistic to test stationarity of series with κ-stable innovations and structural breaks,obtains the asymptotical distribution of the statistic,and proves the consistency of the test.To obtain critic values for the test without the estimation of the index κ,the paper proposes the bootstrap procedures to approximate the distribution,and proves the consistency of the procedures.The simulations demonstrate that the bootstrap test is practical and powerful.展开更多
The paper investigates the sequential observations’ variance change in linear regression model. The procedure is based on a detection function constructed by residual squares of CUSUM and a boundary function which is...The paper investigates the sequential observations’ variance change in linear regression model. The procedure is based on a detection function constructed by residual squares of CUSUM and a boundary function which is designed so that the test has a small probability of false alarm and asymptotic power one. Simulation results show our monitoring procedure performs well when variance change occurs shortly after the monitoring time. The method is still feasible for regression coefficients change or both variance and regression coefficients change problem.展开更多
基金Supported by the National Natural Science Foundation of China (Grant Nos.1092619760972150)
文摘The paper proposes a statistic to test stationarity of series with κ-stable innovations and structural breaks,obtains the asymptotical distribution of the statistic,and proves the consistency of the test.To obtain critic values for the test without the estimation of the index κ,the paper proposes the bootstrap procedures to approximate the distribution,and proves the consistency of the procedures.The simulations demonstrate that the bootstrap test is practical and powerful.
基金Supported by the National Natural Science Foundation of China (Grant Nos.60972150 10926197)the Scienceand Technology Innovation Foundation of Northwestern Polytechnical University (Grant No.2007KJ01033)
文摘The paper investigates the sequential observations’ variance change in linear regression model. The procedure is based on a detection function constructed by residual squares of CUSUM and a boundary function which is designed so that the test has a small probability of false alarm and asymptotic power one. Simulation results show our monitoring procedure performs well when variance change occurs shortly after the monitoring time. The method is still feasible for regression coefficients change or both variance and regression coefficients change problem.
