Topic outline
- GeneralGeneral 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 1Topic 1Introduction 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 2Topic 2Trend ModelsIntroduction, least square estimation, statistical inference in linear trend and non-linear trend models.
- Topic 3Topic 3Model Adequacy CheckingInterpretation of the model, discussion about adequecy checking of trend models.
- Topic 4Topic 4Smoothing ModelsIntroduction, simple exponential smoothing, double exponential smoothing and seasonal exponential smoothing.
- Topic 5Topic 5ARIMA modelsIntroduction, autoregressive model, moving average model and autoregressive integrated moving average models
- Topic 6Topic 6Identification of ARIMA ModelIntroduction,stationary, identify the ARIMA models and diagnostic checking for ARIMA models
- Topic 7Topic 7Seasonal of ARIMA modelsIntroduction, model identification and diagnostic checking.
