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Analysing data

Automatic Model Selection Methods

The purpose of this course is to provide students with an introduction to automatic model selection and its limitations and uses in practical econometric modelling. In addition, the course introduces saturation estimation techniques and considers other approaches.

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This module can be taken as part of a PG Certificate, PG Diploma or Full Masters Program. 

Key Skills

Theoretical properties of automatic model selection.

Using and understanding results from the Autometrics algorithm in PcGive. 

Have a basic understanding of the Autometrics algorithm. 

Saturation estimation, such as indicator, step, and trend indicator saturation. Alternative Lasso based methods.

By the end of this course, participants should have knowledge and ability to: 

Desired Skills

Use automatical model selection to build econometric models. 

Use saturation estimation. 

Present, interpret and analysethe results of automatic model selection. 

Utilise effectively PcGive and the R gets packages. 

By the end of this course, students should be able to: 

Structure

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Automatic Model Selection Models is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.

 

The total number of contact hours is 15 hours. This leaves 85 hours for private study.

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Lectures

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This module consists of 2 - hour lectures per day for 5 days, plus a 1 - hour tutorial per day. 

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 There will be optional clinics on the last day of the course.   

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The dates of each lecture are confirmed closer to the start of each term. If you have any questions about dates, please contact edu@timberlake.co.uk.

  

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