State-space models deal with dynamic time series problems that involve unobserved variables or parameters that describe the evolution in the state of the underlying system. This area of mathematical statistics is relevant to many areas of econometric research, as we often encounter unobserved variables that may be included in a model: output gaps, business cycles, expectational values of certain variables, permanent income streams, ex ante real interest rates, reservation wages, etc. In addition, this framework is also relevant to those who are interested in financial research, as they are used in the application of the many variants of stochastic volatility models.

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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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                           is a coding software for statistical computing. Download here.

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                             is a free, open-source, software. Download here.

                               

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I have a blog titled review of different softwre packages.