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NON-LINEAR REGRESSION MODULE

In econometric time series analysis we usually try to make use of the information that we have at our disposal to describe a relationship between various variables. Such analyses would usually involved time series that extend over quite a long period of time and as a result of which it may be prudent to incorporate certain changes that have occurred to the parameter estimates of the DGP over the said period. The application of nonlinear time series analysis seeks to incorporate changes to the parameters estimates and the use of regime switching models are particularly relevant to cases where we seek to obtain meaningful parameter estimates from a DGP that is subject to changes that are either observed or unobserved.

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The dropbox folder contains exercises, research papers and industry cases that will be covered in linear regression.

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                                                                                        Download here.

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I have a blog titled review of different softwre packages. 

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Module 0:  An Introduction to Non-Linear Regression Course

Module 1:  Paramteric Tests for Detection of Non-Linearity

Module 2:  Non-Paramteric Tests for Detection of Non-Linearity

Module 3:  Non - Linear Autoregressive Model

Module 4:  Markov - Switching Model

Module 5:  Bi-Linear Model

Module 6:  Threhold Autoregressive Model

Module 7:  Self Exiting Threhold Autoregressive Model

Module 8:  Smooth Trandition Autoregressive Model

Module 9:  Artifical Neural Network Model

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