Search
Now showing items 1-5 of 5
Using ANNs and ARIMA Models to Make Accurate Forecasts for Palestinian Official Statistics Based on Simulation and Empirical Applications
(الجامعة الإسلامية - غزة, 2017)
Accuracy of forecasts of economic indicators is a major concern of statistical and economics departments. Over the past three decades there has been growing literature on applications of artificial neural networks (ANNs) ...
The efficiency of artificial neural networks for forecasting in the presence of autocorrelated disturbances
(2016)
We compare three forecasting methods, Artificial Neural Networks (ANNs), Autoregressive Integrated Moving Average (ARIMA) and Regression models. Using computer simulations, the major finding reveals that in the presence ...
Explicit Equations for ACF in Autoregressive Processes In the Presence of Heteroscedasticity Disturbances
(2011)
The autocorrelation function, ACF, is an important guide to the properties of a time series. Explicit equations are derived for ACF in the presence of heteroscedasticity disturbances in pth order autoregressive, AR (p), ...
معادلات محددة لدالة الارتباط الذاتي في حالة عدم تجانس تباينات الأخطاء العشوائية لنماذج الارتباط الذاتي من الرتبة الأولى
(الجامعة الإسلامية - غزة, 2009)
The autocorrelation function, ACF, is an important guide to the properties of a time series. We derive explicit equations for ACF in the presence of heteroscedasticity disturbances in first-order autoregressive, AR(1), ...
Explicit equations for ACF in the presence of heteroscedasticity disturbances in first-order autoregressive models, AR (1)
(2009)
The autocorrelation function, ACF, is an important guide to the properties of a time series. We derive explicit equations for ACF in the presence of heteroscedasticity disturbances in first-order autoregressive, AR (1), ...