This paper investigated the growth and policy implications of Global System for Mobile Communication in Nigeria. Stochastic economic modeling was used to analyze Nigeria＇s time series data. The models were adjudged r...This paper investigated the growth and policy implications of Global System for Mobile Communication in Nigeria. Stochastic economic modeling was used to analyze Nigeria＇s time series data. The models were adjudged reliable before they were used. The components of the model were defined and a prior expectation of the relationship among the variables explained for the purpose of giving the reviewers and users a deep insight into the phenomenon under study. The secondary data used for the study were processed using the E-View for windows electronic packages. The outcome of the empirical and stochastic investigations shows that Global System for Mobile Communication has a positive relationship with output growth in Nigeria. The impact is of a higher magnitude. The usage of Global System for Mobile Telecommunication led to 17 percent rise in the output growth. The findings suggest the need for the Nigerian Communication Commission （NCC） and the federal government of Nigeria to expand tele-density and directly make telephone communications cheap and accessible. To achieve this goal, more licenses should be given to GSM operators in order to allow for healthy competition among them. This will lead to improved quality of services, quality of product and consequently sustain the growth and development of the country.展开更多
The forecasting of time-series data plays an important role in various domains. It is of significance in theory and application to improve prediction accuracy of the time-series data. With the progress in the study of...The forecasting of time-series data plays an important role in various domains. It is of significance in theory and application to improve prediction accuracy of the time-series data. With the progress in the study of time-series, time-series forecasting model becomes more complicated, and consequently great concern has been drawn to the techniques in designing the forecasting model. A modeling method which is easy to use by engineers and may generate good results is in urgent need. In this paper, a gradient-boost AR ensemble learning algorithm (AREL) is put forward. The effectiveness of AREL is assessed by theoretical analyses, and it is demonstrated that this method can build a strong predictive model by assembling a set of AR models. In order to avoid fitting exactly any single training example, an insensitive loss function is introduced in the AREL algorithm, and accordingly the influence of random noise is reduced. To further enhance the capability of AREL algorithm for non-stationary time-series, improve the robustness of algorithm, discourage overfitting, and reduce sensitivity of algorithm to parameter settings, a weighted kNN prediction method based on AREL algorithm is presented. The results of numerical testing on real data demonstrate that the proposed modeling method and prediction method are effective.展开更多
文摘This paper investigated the growth and policy implications of Global System for Mobile Communication in Nigeria. Stochastic economic modeling was used to analyze Nigeria＇s time series data. The models were adjudged reliable before they were used. The components of the model were defined and a prior expectation of the relationship among the variables explained for the purpose of giving the reviewers and users a deep insight into the phenomenon under study. The secondary data used for the study were processed using the E-View for windows electronic packages. The outcome of the empirical and stochastic investigations shows that Global System for Mobile Communication has a positive relationship with output growth in Nigeria. The impact is of a higher magnitude. The usage of Global System for Mobile Telecommunication led to 17 percent rise in the output growth. The findings suggest the need for the Nigerian Communication Commission （NCC） and the federal government of Nigeria to expand tele-density and directly make telephone communications cheap and accessible. To achieve this goal, more licenses should be given to GSM operators in order to allow for healthy competition among them. This will lead to improved quality of services, quality of product and consequently sustain the growth and development of the country.
基金supported by the National Natural Science Foundation of China (Grant No. 60974101)Program for New Century Talents of Education Ministry of China (Grant No. NCET-06-0828)
文摘The forecasting of time-series data plays an important role in various domains. It is of significance in theory and application to improve prediction accuracy of the time-series data. With the progress in the study of time-series, time-series forecasting model becomes more complicated, and consequently great concern has been drawn to the techniques in designing the forecasting model. A modeling method which is easy to use by engineers and may generate good results is in urgent need. In this paper, a gradient-boost AR ensemble learning algorithm (AREL) is put forward. The effectiveness of AREL is assessed by theoretical analyses, and it is demonstrated that this method can build a strong predictive model by assembling a set of AR models. In order to avoid fitting exactly any single training example, an insensitive loss function is introduced in the AREL algorithm, and accordingly the influence of random noise is reduced. To further enhance the capability of AREL algorithm for non-stationary time-series, improve the robustness of algorithm, discourage overfitting, and reduce sensitivity of algorithm to parameter settings, a weighted kNN prediction method based on AREL algorithm is presented. The results of numerical testing on real data demonstrate that the proposed modeling method and prediction method are effective.
