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~person:"Hruschka, Harald"
~person:"Maliar, Serguei"
~type_genre:"Non-commercial literature"
~type_genre:"Working Paper"
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Hruschka, Harald
Maliar, Serguei
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Household savings and monetary policy under individual and aggregate stochastic volatility
Gorodnichenko, Yuriy
;
Maliar, Lilia
;
Maliar, Serguei
; …
-
2020
Persistent link: https://www.econbiz.de/10012504381
Saved in:
2
Deep learning classification : modeling discrete labor choice
Maliar, Lilia
;
Maliar, Serguei
-
2020
Persistent link: https://www.econbiz.de/10012309125
Saved in:
3
Will artificial intelligence replace computational economists any time soon?
Maliar, Lilia
;
Maliar, Serguei
;
Winant, Pablo
-
2019
Persistent link: https://www.econbiz.de/10012196835
Saved in:
4
When the U.S. catches a cold, Canada sneezes : a lower-bound tale told by deep learning
Lepetyuk, Vadym
;
Maliar, Lilia
;
Maliar, Serguei
-
2019
Persistent link: https://www.econbiz.de/10012196854
Saved in:
5
A heterogeneous flexible multinomial probit model of brand choice
Hruschka, Harald
-
2005
Persistent link: https://www.econbiz.de/10003267010
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6
Relevance of functional flexibility for heterogeneous sales response models : a comparison of parametric and seminonparametric models
Hruschka, Harald
-
2004
Persistent link: https://www.econbiz.de/10002179243
Saved in:
7
Homogeneous and latent class versions of the neural net-multinomial logit model (NN-NML) : a semiparametric approach to analyze brand choice
Hruschka, Harald
;
Probst, Markus
;
Fettes, Werner
-
2001
Persistent link: https://www.econbiz.de/10001619754
Saved in:
8
Interpretation aids for multilayer perceptron neutral nets
Hruschka, Harald
-
2001
Persistent link: https://www.econbiz.de/10013408262
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9
Artificial neural net - multinomial logit model : (ANN-MNL); a semiparametric approach to analyze brand choice
Hruschka, Harald
-
1999
Persistent link: https://www.econbiz.de/10013408243
Saved in:
10
Dynamische nichtlineare Referenzpreismodelle mit latenten Variablen
Natter, Martin
-
1994
Persistent link: https://www.econbiz.de/10013408016
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