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isPartOf:"Faculty & research / Insead : working paper series"
subject:"Prognoseverfahren"
~subject:"Bayes-Statistik"
~subject:"Cluster analysis"
~type_genre:"Arbeitspapier"
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Prognoseverfahren
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Faculty & research / Insead : working paper series
Working paper / Department of Econometrics and Business Statistics, Monash University
38
Discussion paper / Tinbergen Institute
28
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18
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Working paper
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Technical report / Sonderforschungsbereich 475 Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund
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Do maximizers predict better than satisficers?
Jain, Kriti
;
Bearden, J. Neil
;
Filipowicz, Allan
-
2011
Persistent link: https://www.econbiz.de/10008901966
Saved in:
2
Human judgement is heavy tailed : empirical evidence and implications for the aggregation of estimates and forecasts
Lobo, Miguel Sousa
;
Yao, Dai
-
2010
Persistent link: https://www.econbiz.de/10008807692
Saved in:
3
A convex optimization approach to modeling consumer heterogeneity in conjoint estimation
Evgeniou, Theodoros
(
contributor
); …
-
2006
-
Rev.
Persistent link: https://www.econbiz.de/10003564727
Saved in:
4
Cluster specific software effort estimation for multi-company datasets
Evgeniou, Theodoros
(
contributor
); …
-
2002
-
[Elektronische Ressource]
Persistent link: https://www.econbiz.de/10001716117
Saved in:
5
A Bayesian design criterion for the dual objective of model discrimination and parameter estimation
Ng, Szu-hui
(
contributor
);
Chick, Stephen E.
(
contributor
)
-
2002
-
[Elektronische Ressource]
Persistent link: https://www.econbiz.de/10001651049
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