Related Articles ( Time series )
Annual Forecasting Using a Hybrid Approach
In this paper, we used a hybrid method based on wavelet transforms and ARIMA models and applied on the time series annual data of rain precipitation in the Province of Erbil-Iraq in millimeters. A sample size has been taken during the period 1970 - 2014.We intended to obtain the ability to explain how ...
Forecasting of Covid-19 deaths in South Africa using the autoregressive integrated moving average time series model
Covid-19 epidemic continues to escalate globally posing life threats to humans. Time series modeling plays a key role for the prediction of data-driven scenarios. A case for Covid-19 pandemic future numbers occurrence is one of the open forecasting scenario for application of the time series modeling. ...
Detection of Outlier in Time Series with Application to Dohuk Dam Using the SCA Statistical System
Outliers are data points or observations that stand out significantly from the rest of the group in terms of size or frequency. They are also referred to as "abnormal data". Before fitting a forecasting model, outliers are often eliminated from the data set, or if not removed, the forecasting model ...
Determine the Best Models for Time Series by using a New Suggested Technique
The proposed method relies on a technique to choose the best model by giving values for the ranks of the model ARMA (p, q), where (p, q) are given the values 0, 1, 2. Every time (ACF) and (PACF) for the series of estimated errors {at} are tested ، and the model which satisfies the two inequalities (7) ...