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Evaluating Automatic Model Selection
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In this paper, we briefly describe the automatic model selection which is provided by Autometrics in the PcGive program. The modeler only needs to specify the initial model and the significance level at which to reduce the model. Then, the algorithm does the rest. The properties of Autometrics are discussed. We also explain its background concepts and try to see whether the model selected by the Autometrics can perform well. For a given data set, we use Autometrics to find a “new” model, and then compare the “new” model with a previously selected one by another modeler. It is an interesting issue to see whether Autometrics can also find models which fit better to the given data.

As an illustration, we choose three examples. It is true that Autometrics is labor saving and always gives us a parsimonious model. It is really an invaluable instrument for social science. But, we still need more examples to strongly support the idea that Autometrics can find a model which fits the data better, just a few examples in this paper is far from enough.

Place, publisher, year, edition, pages
2011. , 30 p.
Keyword [en]
Automatic Model Selection; Autometrics; Seasonal ARIMA; DHSY
URN: urn:nbn:se:uu:diva-154449OAI: diva2:423247
Subject / course
Educational program
Master Programme in Statistics
2011-05-23, 09:20 (English)
Social and Behavioural Science, Law
Available from: 2011-06-15 Created: 2011-06-01 Last updated: 2011-06-15Bibliographically approved

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