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  • Search: subject:"Gradient estimation"
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Year of publication
Subject
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gradient estimation 11 Estimation theory 7 Schätztheorie 7 Simulation 6 Gradient estimation 5 Stochastic process 5 Stochastischer Prozess 5 Monte Carlo simulation 4 Estimation 3 Gradient Estimation 3 Kernel smoothing 3 Least squares cross validation 3 Monte-Carlo-Simulation 3 Regression analysis 3 Regressionsanalyse 3 Schätzung 3 Stochastic gradient estimation 3 Theorie 3 Theory 3 discrete event systems 3 simulation 3 stochastic approximation 3 Conditional Monte Carlo 2 Dimensionality 2 Forecasting model 2 Kernel Smoothing 2 Least Squares Cross Validation 2 Mathematical programming 2 Mathematische Optimierung 2 Neural networks 2 Neuronale Netze 2 Nichtparametrisches Verfahren 2 Nonparametric statistics 2 Prognoseverfahren 2 Sensitivity analysis 2 Sensitivitätsanalyse 2 dimensionality 2 kernel smoothing 2 least squares cross validation 2 mean plots 2
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Online availability
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Undetermined 16 Free 6 CC license 1
Type of publication
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Article 21 Book / Working Paper 5
Type of publication (narrower categories)
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Article in journal 11 Aufsatz in Zeitschrift 11 Working Paper 1
Language
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Undetermined 14 English 12
Author
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Henderson, Daniel J. 7 Parmeter, Christopher F. 7 Fu, Michael 4 Kumbhakar, Subal C. 4 L'Ecuyer, Pierre 4 Hong, L. Jeff 3 Li, Qi 3 Peng, Yijie 3 Glynn, Peter W. 2 Heidergott, Bernd 2 Hu, Jian-Qiang 2 Lam, Henry 2 Nakayama, Marvin K. 2 Yao, Shuang 2 Akşin, Zeynep 1 Andradóttir, Sigrún 1 Borovkova, Svetlana 1 Brekelmans, Ruud 1 Cao, Fang 1 Den Hertog, Dick 1 Driessen, L. 1 Fu, Michael C. 1 Giroux, Nataly 1 Hamers, H.J.M. 1 Hu, Jiaqiao 1 Jiang, Guangxin 1 Karaesmen, Fikri 1 Lei, Lei 1 Li, Haidong 1 Li, Yanjie 1 Liu, Junxian 1 Qu, Huashuai 1 Shahabuddin, Perwez 1 Sun, Qiankun 1 Tuffin, Bruno 1 Volk-Makarewicz, Warren 1 Wang, Tan 1 Xiao, Li 1 Xie, Qichang 1 Zhang, Xuhui 1
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Institution
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Department of Economics, School of Business 2 Institute for the Study of Labor (IZA) 1 Tilburg University, Center for Economic Research 1
Published in...
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Management Science 7 European journal of operational research : EJOR 2 INFORMS journal on computing : JOC ; charting new directions in operations research and computer science ; a journal of the Institute for Operations Research and the Management Sciences 2 IZA Discussion Papers 2 Working Papers / Department of Economics, School of Business 2 Discussion Paper / Tilburg University, Center for Economic Research 1 Econometric reviews 1 Economics Letters 1 European Journal of Operational Research 1 INFORMS journal on computing : JOC 1 Journal of Econometrics 1 Journal of econometrics 1 Journal of management science and engineering 1 Operations research 1 Operations research letters 1 Production and operations management : an international journal of the Production and Operations Management Society 1
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Source
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RePEc 14 ECONIS (ZBW) 11 EconStor 1
Showing 1 - 10 of 26
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Variance reduction for generalized likelihood ratio method by conditional Monte Carlo and randomized Quasi-Monte Carlo methods
Peng, Yijie; Fu, Michael; Hu, Jiaqiao; L'Ecuyer, Pierre; … - In: Journal of management science and engineering 7 (2022) 4, pp. 550-577
The generalized likelihood ratio (GLR) method is a recently introduced gradient estimation method for handling …
Persistent link: https://www.econbiz.de/10014315671
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Large-scale inventory optimization : a recurrent neural networks–inspired simulation approach
Wang, Tan; Hong, L. Jeff - In: INFORMS journal on computing : JOC ; charting new … 35 (2023) 1, pp. 196-215
Persistent link: https://www.econbiz.de/10014327400
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Copula sensitivity analysis for portfolio credit derivatives
Lei, Lei; Peng, Yijie; Fu, Michael; Hu, Jian-Qiang - In: European journal of operational research : EJOR 308 (2023) 1, pp. 455-466
Persistent link: https://www.econbiz.de/10014283065
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Assessing the impact of jumps in an option pricing model : a gradient estimation approach
Volk-Makarewicz, Warren; Borovkova, Svetlana; … - In: European journal of operational research : EJOR 298 (2022) 2, pp. 740-751
Persistent link: https://www.econbiz.de/10013206895
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A new likelihood ratio method for training artificial neural networks
Peng, Yijie; Xiao, Li; Heidergott, Bernd; Hong, L. Jeff; … - In: INFORMS journal on computing : JOC ; charting new … 34 (2022) 1, pp. 638-655
Persistent link: https://www.econbiz.de/10013361323
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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
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Local weighted composite quantile estimation and smoothing parameter selection for nonparametric derivative function
Xie, Qichang; Sun, Qiankun; Liu, Junxian - In: Econometric reviews 39 (2020) 3, pp. 215-233
Persistent link: https://www.econbiz.de/10012181442
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Gradient Based Smoothing Parameter Selection for Nonparametric Regression Estimation
Henderson, Daniel J.; Li, Qi; Parmeter, Christopher F. - Department of Economics, School of Business - 2013
Uncovering gradients is of crucial importance across a broad range of economic environments. Here we consider data-driven bandwidth selection based on the gradient of an unknown regression function. The procedure developed here is automatic and does not require initial estimation of unknown...
Persistent link: https://www.econbiz.de/10010823150
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A simple method to visualize results in nonlinear regression models
Henderson, Daniel J.; Kumbhakar, Subal C.; Parmeter, … - 2012
A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, 'partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple...
Persistent link: https://www.econbiz.de/10010287583
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Cover Image
A simple method to visualize results in nonlinear regression models
Henderson, Daniel J.; Kumbhakar, Subal C.; Parmeter, … - Department of Economics, School of Business - 2012
A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, `partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple...
Persistent link: https://www.econbiz.de/10010823160
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