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isPartOf:"Faculty & research / Insead : working paper series"
subject:"Prognoseverfahren"
~isPartOf:"Cowles Foundation discussion paper"
~isPartOf:"Operations research letters"
~subject:"Conjoint-Analyse"
~subject:"Marketing"
~subject:"Mathematical programming"
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Prognoseverfahren
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Estimation theory
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Schätztheorie
280
Regression analysis
44
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44
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42
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Phillips, Peter C. B.
4
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1
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1
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1
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Chuong Thai Doan
1
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Filipowicz, Allan
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Faculty & research / Insead : working paper series
Cowles Foundation discussion paper
Operations research letters
International journal of forecasting
113
Journal of econometrics
79
Journal of forecasting
71
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45
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Technical report / Sonderforschungsbereich 475 Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund
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Computers & operations research : and their applications to problems of world concern ; an international journal
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NBER working paper series
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Working papers series in theoretical and applied economics
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ECONIS (ZBW)
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1
Solving nonlinear equations with the convex combination of two positive spectral coefficients
Mohammad, Hassan
- In:
Operations research letters
51
(
2023
)
5
,
pp. 515-520
Persistent link: https://www.econbiz.de/10014495879
Saved in:
2
Parametric error bounds for convex approximations of two-stage mixed-integer recourse models with a random second-stage cost vector
Beesten, E. Ruben van
;
Romeijnders, Ward
- In:
Operations research letters
50
(
2022
)
5
,
pp. 541-547
Persistent link: https://www.econbiz.de/10013449443
Saved in:
3
Distributionally robust modeling of optimal control
Shapiro, Alexander
- In:
Operations research letters
50
(
2022
)
5
,
pp. 561-567
Persistent link: https://www.econbiz.de/10013449446
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
A sufficient condition for asymptotically well behaved property of convex polynomials
Li, Xiao-Bing
;
Al-Homidan, Suliman
;
Ansari, Qamrul Hasan
; …
- In:
Operations research letters
49
(
2021
)
4
,
pp. 548-552
Persistent link: https://www.econbiz.de/10012649028
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
The accuracy of less : natural bounds explain why quantity decreases are estimated more accurately than quantity increases
Chandon, Pierre
;
Ordabayeva, Nailya
-
2016
Persistent link: https://www.econbiz.de/10011687289
Saved in:
8
Pitfalls and possibilities in predictive regression
Phillips, Peter C. B.
-
2015
Persistent link: https://www.econbiz.de/10011312325
Saved in:
9
Optimal uncertainty size in distributionally robust inverse covariance estimation
Blanchet, Jose
;
Si, Nian
- In:
Operations research letters
47
(
2019
)
6
,
pp. 618-621
Persistent link: https://www.econbiz.de/10012131899
Saved in:
10
Exact relaxations for parametric robust linear optimization problems
Chuong Thai Doan
- In:
Operations research letters
47
(
2019
)
2
,
pp. 105-109
Persistent link: https://www.econbiz.de/10012003272
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