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accessRights:"restricted"
subject:"Monte Carlo simulation"
~isPartOf:"Operations research letters"
~subject:"Maximum likelihood estimation"
~subject:"Stochastic process"
~type:"article"
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Monte Carlo simulation
Maximum likelihood estimation
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Estimation theory
36
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15
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Operations research letters
Journal of econometrics
104
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39
Journal of business & economic statistics : JBES ; a publication of the American Statistical Association
38
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Studies in nonlinear dynamics and econometrics : SNDE ; quarterly publ. electronically on the internet
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6
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1
Variance comparison between infinitesimal perturbation analysis and likelihood ratio estimators to stochastic gradient
Cui, Zhenyu
;
Liu, Yanchu
;
Wang, Ruodu
- In:
Operations research letters
50
(
2022
)
2
,
pp. 199-204
Persistent link: https://www.econbiz.de/10013192693
Saved in:
2
Iteratively sampling scheme for stochastic optimization with variable number sample path
Hao, Shuang
;
Zhang, Dali
;
Dong, Ming
- In:
Operations research letters
50
(
2022
)
3
,
pp. 347-355
Persistent link: https://www.econbiz.de/10013364106
Saved in:
3
On the optimal design of the randomized unbiased Monte Carlo estimators
Cui, Zhenyu
;
Lee, Chihoon
;
Zhu, Lingjiong
;
Zhu, Yunfan
- In:
Operations research letters
49
(
2021
)
4
,
pp. 477-484
Persistent link: https://www.econbiz.de/10012649016
Saved in:
4
Minimax efficient finite-difference stochastic gradient estimators using black-box function evaluations
Lam, Henry
;
Li, Haidong
;
Zhang, Xuhui
- In:
Operations research letters
49
(
2021
)
1
,
pp. 40-47
Persistent link: https://www.econbiz.de/10012485995
Saved in:
5
Logarithmic sample bounds for Sample Average Approximation with capacity- or budget-constraints
Bugg, Caleb
;
Aswani, Anil
- In:
Operations research letters
49
(
2021
)
2
,
pp. 231-238
Persistent link: https://www.econbiz.de/10012506656
Saved in:
6
When can we improve on sample average approximation for stochastic optimization?
Anderson, Edward J.
;
Nguyen, Harrison
- In:
Operations research letters
48
(
2020
)
5
,
pp. 566-572
Persistent link: https://www.econbiz.de/10012303409
Saved in:
7
Fitting discrete phase-type distribution from censored and truncated observations with pre-specified hazard sequence
Barde, Stephane
;
Ko, Young Myoung
;
Shin, Hayong
- In:
Operations research letters
48
(
2020
)
3
,
pp. 233-239
Persistent link: https://www.econbiz.de/10012254062
Saved in:
8
Relationship between least squares Monte Carlo and approximate linear programming
Nadarajah, Selvaprabu
;
Secomandi, Nicola
- In:
Operations research letters
45
(
2017
)
5
,
pp. 409-414
Persistent link: https://www.econbiz.de/10011774608
Saved in:
9
From estimation to optimization via shrinkage
Davarnia, Danial
;
Cornuéjols, Gérard
- In:
Operations research letters
45
(
2017
)
6
,
pp. 642-646
Persistent link: https://www.econbiz.de/10011783068
Saved in:
10
Stochastic geometric optimization with joint probabilistic constraints
Liu, Jia
;
Lisser, Abdel
;
Chen, Zhiping
- In:
Operations research letters
44
(
2016
)
5
,
pp. 687-691
Persistent link: https://www.econbiz.de/10011596645
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