In time series modeling, the residuals are often checked for white noise and normality. In practice, the useful tests are Ljung Box test. Mcleod Li test and Lin Mudholkar test. In this paper, we present a nonparame...In time series modeling, the residuals are often checked for white noise and normality. In practice, the useful tests are Ljung Box test. Mcleod Li test and Lin Mudholkar test. In this paper, we present a nonparametric approach for checking the residuals of time series models. This approach is based on the maximal correlation coefficient ρ 2 * between the residuals and time t . The basic idea is to use the bootstrap to form the null distribution of the statistic ρ 2 * under the null hypothesis H 0:ρ 2 * =0. For calculating ρ 2 * , we proposes a ρ algorithm, analogous to ACE procedure. Power study shows this approach is more powerful than Ljung Box test. Meanwhile, some numerical results and two examples are reported in this paper.展开更多
In this article a new approach for checking the adequacy of GARCH-type models in time series was proposed. The resulted tests involve weight functions, which provide them with the flexibility in choosing scores to enh...In this article a new approach for checking the adequacy of GARCH-type models in time series was proposed. The resulted tests involve weight functions, which provide them with the flexibility in choosing scores to enhance power performance. The choice of weight functions and the power properties of the tests are studied. For a large number of alternatives, asymptotically distribution-free maximin test is constructed. The tests are asymptotically chi-squared under the null hypothesis and easy to implement. Simulation results indicate that the tests perform well.展开更多
The coronavirus outbreak is the most notable world crisis since the SecondWorldWar.The pandemic that originated from Wuhan,China in late 2019 has affected all the nations of the world and triggered a global economic c...The coronavirus outbreak is the most notable world crisis since the SecondWorldWar.The pandemic that originated from Wuhan,China in late 2019 has affected all the nations of the world and triggered a global economic crisis whose impact will be felt for years to come.This necessitates the need to monitor and predict COVID-19 prevalence for adequate control.The linear regression models are prominent tools in predicting the impact of certain factors on COVID-19 outbreak and taking the necessary measures to respond to this crisis.The data was extracted from the NCDC website and spanned from March 31,2020 to May 29,2020.In this study,we adopted the ordinary least squares estimator to measure the impact of travelling history and contacts on the spread of COVID-19 in Nigeria and made a prediction.The model was conducted before and after travel restriction was enforced by the Federal government of Nigeria.The fitted model fitted well to the dataset and was free of any violation based on the diagnostic checks conducted.The results show that the government made a right decision in enforcing travelling restriction because we observed that travelling history and contacts made increases the chances of people being infected with COVID-19 by 85%and 88%respectively.This prediction of COVID-19 shows that the government should ensure that most travelling agency should have better precautions and preparations in place before re-opening.展开更多
文摘In time series modeling, the residuals are often checked for white noise and normality. In practice, the useful tests are Ljung Box test. Mcleod Li test and Lin Mudholkar test. In this paper, we present a nonparametric approach for checking the residuals of time series models. This approach is based on the maximal correlation coefficient ρ 2 * between the residuals and time t . The basic idea is to use the bootstrap to form the null distribution of the statistic ρ 2 * under the null hypothesis H 0:ρ 2 * =0. For calculating ρ 2 * , we proposes a ρ algorithm, analogous to ACE procedure. Power study shows this approach is more powerful than Ljung Box test. Meanwhile, some numerical results and two examples are reported in this paper.
基金supported by a grant from the Research Grants Council of Hong Kong.Jianhong Wu was also supported by a grant from Humanities & Social Sciences in Chinese University (07JJD790154)the Youth Talent Foundation of Zhejiang GongShang University (Q09-12)
文摘In this article a new approach for checking the adequacy of GARCH-type models in time series was proposed. The resulted tests involve weight functions, which provide them with the flexibility in choosing scores to enhance power performance. The choice of weight functions and the power properties of the tests are studied. For a large number of alternatives, asymptotically distribution-free maximin test is constructed. The tests are asymptotically chi-squared under the null hypothesis and easy to implement. Simulation results indicate that the tests perform well.
文摘The coronavirus outbreak is the most notable world crisis since the SecondWorldWar.The pandemic that originated from Wuhan,China in late 2019 has affected all the nations of the world and triggered a global economic crisis whose impact will be felt for years to come.This necessitates the need to monitor and predict COVID-19 prevalence for adequate control.The linear regression models are prominent tools in predicting the impact of certain factors on COVID-19 outbreak and taking the necessary measures to respond to this crisis.The data was extracted from the NCDC website and spanned from March 31,2020 to May 29,2020.In this study,we adopted the ordinary least squares estimator to measure the impact of travelling history and contacts on the spread of COVID-19 in Nigeria and made a prediction.The model was conducted before and after travel restriction was enforced by the Federal government of Nigeria.The fitted model fitted well to the dataset and was free of any violation based on the diagnostic checks conducted.The results show that the government made a right decision in enforcing travelling restriction because we observed that travelling history and contacts made increases the chances of people being infected with COVID-19 by 85%and 88%respectively.This prediction of COVID-19 shows that the government should ensure that most travelling agency should have better precautions and preparations in place before re-opening.
