STAT3702 Stochastic Processes

Introduction to Stochastic Processes; Markov Chains; Fundamental concepts in Time Series; Model Stationary and Nonstationary; Model specification; Model estimation; Model diagnostics and Model forecasting in Time Series.

This topic aims to build upon the principles of applied probability modelling to extend to models of complex processes.

1. Understand the concepts of stochastic processes and time series analysis in the time domain respectively
2. Determine and apply appropriate time series models for the real life datasets
3. Have developed skills in statistical computing of time series or stochastic processes related problems