Module Directory

 

Module Description

 
 
Module Name
Module Code
Lecture Hrs
Practical Hrs
Credits
Time Series Analysis and Business Forecasting (Special paper)
STAT3015Y(5)*
3
0
6

Description
Examples of time series. Time series plot. Model-building strategy. Classical trend and seasonal model. Additive and multiplicative models. Decomposition. Exponential smoothing. Estimation. Forecasting using Holt-Winters method. Time series and stochastic processes. Autocovariance function. Random walk. 5 Moving Average. White Noise. Stationarity. Models for stationary time series : general linear process, MA processes. AR processes. Invertibility. Box-Jenkins methods. ARIMA and SARIMA processes. Models for non-stationary time series. Differencing. Model specification. Properties of sample acf and pacf. Nonstationarity. AIC criterion. Model Estimation and diagnostics. Residual analysis. Box-Pierce and Ljung- Box statistics. Forecasting. Using R Statistical Language for time series analysis.
Faculty Department
FACULTY OF SOCIAL SCIENCES AND HUMANITIES Department of Economics and Statistics
Contact Details
Administrative assistant: DILMAHOMED BOCUS Bibi Swaleha
Telephone: 4037400
Email: s.dilmahomed@uom.ac.mu
 

 


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