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Erschienen in:
Short Term Load Forecasting in the Industry for Establishing Consumption Baselines: A French Case Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Constructing Graphical Models via the Focused Information Criterion

verfasst von : Gerda Claeskens, Eugen Pircalabelu, Lourens Waldorp

Erschienen in: Modeling and Stochastic Learning for Forecasting in High Dimensions

Verlag: Springer International Publishing

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Abstract

A focused information criterion is developed to estimate undirected graphical models where for each node in the graph a generalized linear model is put forward conditioned upon the other nodes in the graph. The proposed method selects a graph with a small estimated mean squared error for a user-specified focus, which is a function of the parameters in the generalized linear models, by selecting an appropriate model at each node. For situations where the number of nodes is large in comparison with the number of cases, the procedure performs penalized estimation with quadratic approximations to several popular penalties. To show the procedure’s applicability and usefulness we have applied it to two datasets involving voting behavior of U.S. senators and to a clinical dataset on psychopathology.

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Vorheriges Kapitel Modelling and Forecasting Daily Electricity Load via Curve Linear Regression
Nächstes Kapitel Fully Nonparametric Short Term Forecasting Electricity Consumption
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Metadaten
Titel
Constructing Graphical Models via the Focused Information Criterion
verfasst von
Gerda Claeskens
Eugen Pircalabelu
Lourens Waldorp
Copyright-Jahr
2015
Buch
Modeling and Stochastic Learning for Forecasting in High Dimensions

Print ISBN: 978-3-319-18731-0

Electronic ISBN: 978-3-319-18732-7

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-18732-7_4