Macro-economic Time Series Modeling and Interaction Networks
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Kronberger:evoapps11,
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author = "Gabriel Kronberger and Stefan Fink and
Michael Kommenda and Michael Affenzeller",
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title = "Macro-economic Time Series Modeling and Interaction
Networks",
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booktitle = "Applications of Evolutionary Computing,
EvoApplications 2011: {EvoCOMNET}, {EvoFIN}, {EvoHOT},
{EvoMUSART}, {EvoSTIM}, {EvoTRANSLOG}",
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year = "2011",
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month = "27-29 " # apr,
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editor = "Cecilia {Di Chio} and Anthony Brabazon and
Gianni {Di Caro} and Rolf Drechsler and Marc Ebner and
Muddassar Farooq and Joern Grahl and Gary Greenfield and
Christian Prins and Juan Romero and
Giovanni Squillero and Ernesto Tarantino and Andrea G. B. Tettamanzi and
Neil Urquhart and A. Sima Uyar",
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series = "LNCS",
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volume = "6625",
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publisher = "Springer Verlag",
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address = "Turin, Italy",
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publisher_address = "Berlin",
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pages = "101--110",
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organisation = "EvoStar",
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keywords = "genetic algorithms, genetic programming, Finance,
Econometrics",
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isbn13 = "978-3-642-20519-4",
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DOI = "doi:10.1007/978-3-642-20520-0_11",
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abstract = "Macro-economic models describe the dynamics of
economic quantities. The estimations and forecasts
produced by such models play a substantial role for
financial and political decisions. In this contribution
we describe an approach based on genetic programming
and symbolic regression to identify variable
interactions in large datasets. In the proposed
approach multiple symbolic regression runs are executed
for each variable of the dataset to find potentially
interesting models. The result is a variable
interaction network that describes which variables are
most relevant for the approximation of each variable of
the dataset. This approach is applied to a
macro-economic dataset with monthly observations of
important economic indicators in order to identify
potentially interesting dependencies of these
indicators. The resulting interaction network of
macro-economic indicators is briefly discussed and two
of the identified models are presented in detail. The
two models approximate the help wanted index and the
CPI inflation in the US.",
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notes = "Part of \cite{DiChio:2011:evo_b} EvoApplications2011
held inconjunction with EuroGP'2011, EvoCOP2011 and
EvoBIO2011",
- }
Genetic Programming entries for
Gabriel Kronberger
Stefan Fink
Michael Kommenda
Michael Affenzeller
Citations