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isPartOf:"Applying maximum entropy to econometric problems"
subject:"Monte Carlo simulation"
~isPartOf:"Operations research"
~subject:"Schätzung"
~subject:"Stochastischer Prozess"
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Applying maximum entropy to econometric problems
Operations research
Journal of econometrics
281
Journal of business & economic statistics : JBES ; a publication of the American Statistical Association
158
Economics letters
137
Econometric reviews
81
Applied economics letters
67
Economic modelling
67
Discussion paper / Tinbergen Institute
66
Discussion paper series / IZA
64
NBER Working Paper
62
Empirical economics : a journal of the Institute for Advanced Studies, Vienna, Austria
59
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57
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47
Econometric theory
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Studies in nonlinear dynamics and econometrics : SNDE ; quarterly publ. electronically on the internet
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Working paper / Department of Econometrics and Business Statistics, Monash University
44
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The econometrics journal
41
Computational economics
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Empirical economics : a quarterly journal of the Institute for Advanced Studies
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SFB 649 discussion paper
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Finance research letters
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The review of economics and statistics
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1
High-order steady-state diffusion approximations
Braverman, Anton
;
Dai, J. G.
;
Fang, Xiao
- In:
Operations research
72
(
2024
)
2
,
pp. 604-616
Persistent link: https://www.econbiz.de/10014520812
Saved in:
2
Enhanced balancing of bias-variance tradeoff in stochastic estimation : a minimax perspective
Lam, Henry
;
Zhang, Xinyu
;
Zhang, Xuhui
- In:
Operations research
71
(
2023
)
6
,
pp. 2352-2373
Persistent link: https://www.econbiz.de/10014445044
Saved in:
3
Stability and sample-based approximations of composite stochastic optimization problems
Dentcheva, Darinka
;
Lin, Yang
;
Penev, Spiridon
- In:
Operations research
71
(
2023
)
5
,
pp. 1871-1888
Persistent link: https://www.econbiz.de/10014393285
Saved in:
4
Computation of exact bootstrap confidence intervals : complexity and deterministic algorithms
Bertsimas, Dimitris
;
Sturt, Bradley
- In:
Operations research
68
(
2020
)
3
,
pp. 949-964
Persistent link: https://www.econbiz.de/10012234527
Saved in:
5
Maximum likelihood estimation by Monte Carlo simulation : toward data-driven stochastic modeling
Peng, Yijie
;
Fu, Michael
;
Heidergott, Bernd
;
Lam, Henry
- In:
Operations research
68
(
2020
)
6
,
pp. 1896-1912
Persistent link: https://www.econbiz.de/10012392175
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6
Divide and conquer : recursive likelihood function integration for hidden Markov models with continuous latent variables
Reich, Gregor
- In:
Operations research
66
(
2018
)
6
,
pp. 1457-1470
Persistent link: https://www.econbiz.de/10011971637
Saved in:
7
Unbiased estimators and multilevel Monte Carlo
Vihola, Matti
- In:
Operations research
66
(
2018
)
2
,
pp. 448-462
Persistent link: https://www.econbiz.de/10011845993
Saved in:
8
A new unbiased stochastic derivative estimator for discontinuous sample performances with structural parameters
Peng, Yijie
;
Fu, Michael
;
Hu, Jian-Qiang
;
Heidergott, Bernd
- In:
Operations research
66
(
2018
)
2
,
pp. 487-499
Persistent link: https://www.econbiz.de/10011845997
Saved in:
9
Kernel smoothing for nested estimation with application to portfolio risk measurement
Hong, L. Jeff
;
Juneja, Sandeep
;
Liu, Guangwu
- In:
Operations research
65
(
2017
)
3
,
pp. 657-673
Persistent link: https://www.econbiz.de/10011691391
Saved in:
10
An expectation-maximization method to estimate a rank-based choice model of demand
Van Ryzin, Garrett
;
Vulcano, Gustavo
- In:
Operations research
65
(
2017
)
2
,
pp. 396-407
Persistent link: https://www.econbiz.de/10011673157
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