In the area of time series modelling, several applications are encountered in real-life that involve analysis of count time series data. The distribution characteristics and dependence structure are the major issues t...In the area of time series modelling, several applications are encountered in real-life that involve analysis of count time series data. The distribution characteristics and dependence structure are the major issues that arise while specifying a modelling strategy to handle the analysis of those kinds of data. Owing to the numerous applications there is a need to develop models that can capture these features. However, accounting for both aspects simultaneously presents complexities while specifying a modeling strategy. In this paper, an alternative statistical model able to deal with issues of discreteness, overdispersion, serial correlation over time is proposed. In particular, we adopt a branching mechanism to develop a first-order stationary negative binomial autoregressive model. Inference is based on maximum likelihood estimation and a simulation study is conducted to evaluate the performance of the proposed approach. As an illustration, the model is applied to a real-life dataset in crime analysis.展开更多
The Poisson integer-valued GARCH model is a popular tool in modeling time series of counts.The commonly used maximum likelihood estimator is strongly influenced by outliers,so there is a need to develop a robust M-est...The Poisson integer-valued GARCH model is a popular tool in modeling time series of counts.The commonly used maximum likelihood estimator is strongly influenced by outliers,so there is a need to develop a robust M-estimator for this model.This paper has three aims.First,the authors propose a new loss function,which is a hybrid of the tri-weight loss for relatively small errors and the exponential squared loss for relatively large ones.Second,Mallows’quasi-likelihood estimator(MQLE)is proposed as an M-estimator and its existence,uniqueness,consistency and asymptotic normality are established.In addition,a data-adaptive algorithm for computing MQLE is given based on a datadriven selection of tuning parameters in the loss function.Third,simulation studies and analysis of a real example are conducted to illustrate the performance of the new estimator,and a comparison with existing estimators is made.展开更多
This paper discusses our collaboration work with government officers in the health department of Seoul during the COVID-19 pandemic.First,we focus on short-term forecasting for the number of new confirmed cases and se...This paper discusses our collaboration work with government officers in the health department of Seoul during the COVID-19 pandemic.First,we focus on short-term forecasting for the number of new confirmed cases and severe cases.Second,we focus on understanding how much of the current infections has been affected by external influx from neighborhood areas or internal transmission within the area.This understanding may be important because it is linked to the government policy determining nonpharmaceutical interventions.To obtain the decomposition of the effect,districts of Seoul should be considered simultaneously,and multivariate time series models are used.Third,we focus on predicting the number of new weekly confirmed cases for each district in Seoul.This detailed prediction may be important to the government policy on resource allocation.We consider an ensemble method to overcome poor prediction performance of simple models.This paper presents the methodological details and analysis results of the study.展开更多
In the measurement of fluorescent lifetime based on time correlation-single photon counting technique by means of TAC, due to the contamination of multi-photons a deviation of fluorescent lifetime measured from the ex...In the measurement of fluorescent lifetime based on time correlation-single photon counting technique by means of TAC, due to the contamination of multi-photons a deviation of fluorescent lifetime measured from the expected value is experimentally studied. A correction function instead of a simple exponential function is used to fit the experiment data. The validation of the correction function is checked using the experimental data of several test samples： YAP, NaI（T1） and LSO. The results show that the correction function well fits the data and the reasonable fluorescent lifetimes are obtained.展开更多
文摘In the area of time series modelling, several applications are encountered in real-life that involve analysis of count time series data. The distribution characteristics and dependence structure are the major issues that arise while specifying a modelling strategy to handle the analysis of those kinds of data. Owing to the numerous applications there is a need to develop models that can capture these features. However, accounting for both aspects simultaneously presents complexities while specifying a modeling strategy. In this paper, an alternative statistical model able to deal with issues of discreteness, overdispersion, serial correlation over time is proposed. In particular, we adopt a branching mechanism to develop a first-order stationary negative binomial autoregressive model. Inference is based on maximum likelihood estimation and a simulation study is conducted to evaluate the performance of the proposed approach. As an illustration, the model is applied to a real-life dataset in crime analysis.
基金supported by Research Start-up Fund of Changchun Normal UniversityNatural Science Found of Changchun Normal University under Grant No.2018-004+1 种基金the National Natural Science Foundation of China under Grant Nos.11871027 and 11731015Cultivation Plan for Excellent Young Scholar Candidates of Jilin University。
文摘The Poisson integer-valued GARCH model is a popular tool in modeling time series of counts.The commonly used maximum likelihood estimator is strongly influenced by outliers,so there is a need to develop a robust M-estimator for this model.This paper has three aims.First,the authors propose a new loss function,which is a hybrid of the tri-weight loss for relatively small errors and the exponential squared loss for relatively large ones.Second,Mallows’quasi-likelihood estimator(MQLE)is proposed as an M-estimator and its existence,uniqueness,consistency and asymptotic normality are established.In addition,a data-adaptive algorithm for computing MQLE is given based on a datadriven selection of tuning parameters in the loss function.Third,simulation studies and analysis of a real example are conducted to illustrate the performance of the new estimator,and a comparison with existing estimators is made.
基金This studywas exempted from review by the Institutional ReviewBoard(IRB)of Seoul National University(SNU IRB no.21-08-109)because the data were aggregated and anonymizedThis work was supported by the National Research Foundation of Korea(BK21 Center for Integrative Response to Health Disasters,Graduate School of Public Health,Seoul National University)(NO.4199990514025)Woojoo Lee was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(no.2021R1A2C1014409).
文摘This paper discusses our collaboration work with government officers in the health department of Seoul during the COVID-19 pandemic.First,we focus on short-term forecasting for the number of new confirmed cases and severe cases.Second,we focus on understanding how much of the current infections has been affected by external influx from neighborhood areas or internal transmission within the area.This understanding may be important because it is linked to the government policy determining nonpharmaceutical interventions.To obtain the decomposition of the effect,districts of Seoul should be considered simultaneously,and multivariate time series models are used.Third,we focus on predicting the number of new weekly confirmed cases for each district in Seoul.This detailed prediction may be important to the government policy on resource allocation.We consider an ensemble method to overcome poor prediction performance of simple models.This paper presents the methodological details and analysis results of the study.
文摘In the measurement of fluorescent lifetime based on time correlation-single photon counting technique by means of TAC, due to the contamination of multi-photons a deviation of fluorescent lifetime measured from the expected value is experimentally studied. A correction function instead of a simple exponential function is used to fit the experiment data. The validation of the correction function is checked using the experimental data of several test samples： YAP, NaI（T1） and LSO. The results show that the correction function well fits the data and the reasonable fluorescent lifetimes are obtained.
