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
Cancer continues to be a major health problem in the world. During 2018, there were 9.6 million deaths and 18.1 million new cases registered across the globe. It is estimated that one in 5 men and one in 6 women will ...Cancer continues to be a major health problem in the world. During 2018, there were 9.6 million deaths and 18.1 million new cases registered across the globe. It is estimated that one in 5 men and one in 6 women will develop cancer during their lifetime. This disease kills one in 8 men and one in 11 women. Developing countries have seen an increase in cancer occurrence and change in type of cancers due to change in social and economic conditions. The objective of this research was to further evaluate 1659 specimens for anatomical pathology testing. The data was collected from the records of the pathological anatomy laboratory at the Mohamed V Hospital in Meknes, Morocco. It is one-year study period (January-December 2013). Results of the anatomy pathology exam showed cancer positive for 9.6% of specimens;inconclusive for 1%;and negative for 66.2%. For all specimens, the most analyzed organs are breast with 29.7%;skin with 21.3%;cervical with 2.6%. For cancer patients, the most affected organs are skin (21.3%) and breast (29.7%). For cancer patients, Neoplasm is present in 9.3% of patients. Patients with metastatic cancer represent 0.3%. Patients with non-neoplastic lesions represent 66.2%. 1% of patients represent uncertain results. Additional immunohistochemistry research is needed before conclusive recommendations are made.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.
文摘Cancer continues to be a major health problem in the world. During 2018, there were 9.6 million deaths and 18.1 million new cases registered across the globe. It is estimated that one in 5 men and one in 6 women will develop cancer during their lifetime. This disease kills one in 8 men and one in 11 women. Developing countries have seen an increase in cancer occurrence and change in type of cancers due to change in social and economic conditions. The objective of this research was to further evaluate 1659 specimens for anatomical pathology testing. The data was collected from the records of the pathological anatomy laboratory at the Mohamed V Hospital in Meknes, Morocco. It is one-year study period (January-December 2013). Results of the anatomy pathology exam showed cancer positive for 9.6% of specimens;inconclusive for 1%;and negative for 66.2%. For all specimens, the most analyzed organs are breast with 29.7%;skin with 21.3%;cervical with 2.6%. For cancer patients, the most affected organs are skin (21.3%) and breast (29.7%). For cancer patients, Neoplasm is present in 9.3% of patients. Patients with metastatic cancer represent 0.3%. Patients with non-neoplastic lesions represent 66.2%. 1% of patients represent uncertain results. Additional immunohistochemistry research is needed before conclusive recommendations are made.
