the rational expectations permanent income hypothesis implies that consumption follows a martingale. however, most empirical tests have rejected the hypothesis. those empirical tests are based on linear models. if the data generating process is non-linear, conventional tests may not assess some of the randomness properly. as a result, inference based on conventional tests of linear models can b...

A multiple linear regression and ARIMA hybrid model is proposed for new bug prediction depending upon resolved bugs and other available parameters of the open source software bug report. Analysis of last five year bug report data of a open source software “worldcontrol” is done to identify the trends followed by various parameters. Bug report data has been categorized on monthly basis and forec...

Background and Objectives: Efficient cost management in hospitals’ pharmaceutical inventories have the potential to remarkably contribute to optimization of overall hospital expenditures. To this end, reliable forecasting models for accurate prediction of future pharmaceutical demands are instrumental. While the linear methods are frequently used for forecasting purposes chiefly due to their si...

Traditionally, the autoregressive integrated moving average (ARIMA) model has been one of the most widely used linear models in time series forecasting. However, the ARIMA model cannot easily capture the nonlinear patterns. Support vector machines (SVMs), a novel neural network technique, have been successfully applied in solving nonlinear regression estimation problems. Therefore, this investi...

The predictability of network traffic is a significant interest in many domains such as congestion control, admission control, and network management. An accurate traffic prediction model should have the ability to capture prominent traffic characteristics, such as long-range dependence (LRD) and self-similarity in the large time scale, multifractal in small time scale. In this paper we propose...

Autoregressive integrated moving average (ARIMA) is one of the popular linear models in time series forecasting during the past three decades. Recent research activities in forecasting with arti/cial neural networks (ANNs) suggest that ANNs can be a promising alternative to the traditional linear methods. ARIMA models and ANNs are often compared with mixed conclusions in terms of the superiorit...

background and objectives: efficient cost management in hospitals’ pharmaceutical inventories have thepotential to remarkably contribute to optimization of overall hospital expenditures. to this end, reliable forecasting models for accurate prediction of future pharmaceutical demands are instrumental. while the linear methods are frequently used for forecasting purposes chiefly due to their sim...

As to the established gray model based on the linear time-variant and individual prediction model of ARIMA, this article constructs the combined forecasting model based on the gray model and the time series model by means of relative error weighing. This prediction indicates that both the gray model and ARIMA model exert efficient function on the Torpedo development cost prediction, and the com...

In business, industry and government agencies, anticipating future behavior that involves many critical variables for nation wealth creation is vitally important, thus the necessity to make precise decision by the policy makers is really essential. Consequently, an accurate and reliable forecast system is needed to compose such predictions. Accordingly, the aim of this research is to develop a ...

The demographic process cannot be inseparable from the mortality rate. appropriate models for forecasting rates are essential in assisting governments, companies, and other agencies formulating policies or making decisions. As one of countries with highest death rate, Japan is influenced by several factors. This research uses Generalized Lee-Carter Model), which developments (LC) model. model w...