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Constrained optimization approaches to estimation of structural models
Su, Che-Lin; Judd, Kenneth L. - 2011
that our approach and the NFXP algorithm solve the same estimation problem, and yield the same estimates. Computationally …
Persistent link: https://www.econbiz.de/10008665893
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Identification in models with discrete variables
Lafférs, Lukáš - 2013
Persistent link: https://www.econbiz.de/10009688445
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A method for finding the maximal set in excess demand
Andersson, Tommy (contributor) - 2014
Persistent link: https://www.econbiz.de/10010256219
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Constrained optimization approaches to estimation of structural models : comment
Iskhakov, Fedor; Lee, Jinhyuk; Rust, John; Schjerning, … - 2015
Persistent link: https://www.econbiz.de/10010501993
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A method for finding the maximal set in excess demand
Andersson, Tommy; Erlanson, Albin; Gudmundsson, Jens; … - In: Economics letters 125 (2014) 1, pp. 18-20
Persistent link: https://www.econbiz.de/10010504790
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A Bayesian model and numerical algorithm for CBM availability maximization
Jiang, Rui; Kim, Michael Jong; Makis, Viliam - 2012
Persistent link: https://www.econbiz.de/10009581403
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Constrained Optimization Approaches to Estimation of Structural Models : Comment
Iskhakov, Fedor - 2015
fixed point algorithm that relies on successive approximations. We re-do their comparison using the more efficient version …
Persistent link: https://www.econbiz.de/10013025765
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Mallows-smoothed distribution over rankings approach for modeling choice
Désir, Antoine; Goyal, Vineet; Jagabathula, Srikanth; … - In: Operations research 69 (2021) 4, pp. 1206-1227
Persistent link: https://www.econbiz.de/10012625180
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Constrained Optimization Approaches to Estimation of Structural Models
Su, Che-Lin; Judd, Kenneth L. - 2012
that our approach and the NFXP algorithm solve the same estimation problem, and yield the same estimates. Computationally …
Persistent link: https://www.econbiz.de/10014220860
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Smoothing-based initialization for learning-to-forecast algorithms
Berardi, Michele; Galimberti, Jaqueson K. - 2017
consistent with the statistical properties of the learning algorithm. Our method is generically formulated to cover different …
Persistent link: https://www.econbiz.de/10011619472