Objective: Through the application of the physiological indicator of heart rate variability by some equipments, to assess the psychological quality objectively, quickly and accurately instead of subjectively in the cu...Objective: Through the application of the physiological indicator of heart rate variability by some equipments, to assess the psychological quality objectively, quickly and accurately instead of subjectively in the current methods of the assessment. Methods: Apply the new psychological assessment system to collect the signal of heart rate variability which will be converted to waveforms in time-domain and frequency-domain to analyze people's psychological state. Results: According to heart rate variability parameters in the time domain and frequency domain, we can analyze the autonomic nervous system functions objectively and accurately, then assess mental state. Conclusion: Heart rate variability plays an important role in the psychological assessment system, which has broad prospects for the future development.展开更多
By an interpolation method,an intrinsic Harnack estimate and some supestimates are established for nonnegative solutions to a general singular parabolic equation.
We consider the periodic generalized autoregressive conditional heteroskedasticity(P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH mo...We consider the periodic generalized autoregressive conditional heteroskedasticity(P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH model. Under some mild conditions, we establish the asymptotic results of proposed estimator.The Monte Carlo simulation is presented to assess the performance of proposed estimator. Numerical study results show that our proposed estimation outperforms other existing methods for heavy tailed distributions.The proposed methodology is also illustrated by Va R on stock price data.展开更多
When dealing with regression analysis,heteroscedasticity is a problem that the authors have to face with.Especially if little information can be got in advance,detection of heteroscedasticity as well as estimation of ...When dealing with regression analysis,heteroscedasticity is a problem that the authors have to face with.Especially if little information can be got in advance,detection of heteroscedasticity as well as estimation of statistical models could be even more difficult.To this end,this paper proposes a quantile difference method(QDM) that can effectively estimate the heteroscedastic function.This method,being completely free from the estimation of mean regression function,is simple,robust and easy to implement.Moreover,the QDM method enables the detection of heteroscedasticity without any restrictions on error terms,consequently being widely applied.What is worth mentioning is that based on the proposed approach estimators of both mean regression function and heteroscedastic function can be obtained.In the end,the authors conduct some simulations to examine the performance of the proposed methods and use a real data to make an illustration.展开更多
文摘Objective: Through the application of the physiological indicator of heart rate variability by some equipments, to assess the psychological quality objectively, quickly and accurately instead of subjectively in the current methods of the assessment. Methods: Apply the new psychological assessment system to collect the signal of heart rate variability which will be converted to waveforms in time-domain and frequency-domain to analyze people's psychological state. Results: According to heart rate variability parameters in the time domain and frequency domain, we can analyze the autonomic nervous system functions objectively and accurately, then assess mental state. Conclusion: Heart rate variability plays an important role in the psychological assessment system, which has broad prospects for the future development.
基金Project supported by the Fujian Provincial Natural Science Foundation of China(No.2009J01009)the Natural Science Foundation of Jimei University
文摘By an interpolation method,an intrinsic Harnack estimate and some supestimates are established for nonnegative solutions to a general singular parabolic equation.
基金supported by National Natural Science Foundation of China(Grant No.11371354)Key Laboratory of Random Complex Structures and Data Science+2 种基金Chinese Academy of Sciences(Grant No.2008DP173182)National Center for Mathematics and Interdisciplinary SciencesChinese Academy of Sciences
文摘We consider the periodic generalized autoregressive conditional heteroskedasticity(P-GARCH) process and propose a robust estimator by composite quantile regression. We study some useful properties about the P-GARCH model. Under some mild conditions, we establish the asymptotic results of proposed estimator.The Monte Carlo simulation is presented to assess the performance of proposed estimator. Numerical study results show that our proposed estimation outperforms other existing methods for heavy tailed distributions.The proposed methodology is also illustrated by Va R on stock price data.
基金supported by the National Natural Science Foundation of China under Grant No.11271368the Major Program of Beijing Philosophy and Social Science Foundation of China under Grant No.15ZDA17+3 种基金the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant No.20130004110007the Key Program of National Philosophy and Social Science Foundation under Grant No.13AZD064the Fundamental Research Funds for the Central Universities,and the Research Funds of Renmin University of China under Grant No.15XNL008the Project of Flying Apsaras Scholar of Lanzhou University of Finance & Economics
文摘When dealing with regression analysis,heteroscedasticity is a problem that the authors have to face with.Especially if little information can be got in advance,detection of heteroscedasticity as well as estimation of statistical models could be even more difficult.To this end,this paper proposes a quantile difference method(QDM) that can effectively estimate the heteroscedastic function.This method,being completely free from the estimation of mean regression function,is simple,robust and easy to implement.Moreover,the QDM method enables the detection of heteroscedasticity without any restrictions on error terms,consequently being widely applied.What is worth mentioning is that based on the proposed approach estimators of both mean regression function and heteroscedastic function can be obtained.In the end,the authors conduct some simulations to examine the performance of the proposed methods and use a real data to make an illustration.
