Topic outline
- General
General
Lecturer : Ani Shabri
Semester : Semester II 2013/2014 Synopsis :
The course is designed to provide students to learn time series modelling in theory and practice with emphasis on practical aspects of time series analysis. Methods are hierarchically introduced-starting with terminology and exploratory graphics, progressing to descriptive statistics, and ending with basic modelling procedures. The time series modelling will start with reviewing the fundamental concepts in regression, exponential smoothing and general class of Box Jenkins models.
This work, SSH4113 Time Series by Ani Shabri is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License - Topic 1
Topic 1
Introduction to ForecastingThe nature and uses of forecasts, some examples of time series and resources for forecasting. Introduction, graphical displays, use data transformations for trend time series. - Topic 2
Topic 2
Trend ModelsIntroduction, least square estimation, statistical inference in linear trend and non-linear trend models. - Topic 3
Topic 3
Model Adequacy CheckingInterpretation of the model, discussion about adequecy checking of trend models. - Topic 4
Topic 4
Smoothing ModelsIntroduction, simple exponential smoothing, double exponential smoothing and seasonal exponential smoothing. - Topic 5
Topic 5
ARIMA modelsIntroduction, autoregressive model, moving average model and autoregressive integrated moving average models - Topic 6
Topic 6
Identification of ARIMA ModelIntroduction,stationary, identify the ARIMA models and diagnostic checking for ARIMA models - Topic 7
Topic 7
Seasonal of ARIMA modelsIntroduction, model identification and diagnostic checking.