Search Results - subject:"gradient estimation"

A Simple Method to Visualize Results in Nonlinear Regression Models

Henderson, Daniel J.; Kumbhakar, Subal C.; Parmeter, … - Institute for the Study of Labor (IZA) - 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/10010705564

Gradient-based smoothing parameter selection for nonparametric regression estimation

Henderson, Daniel J.; Li, Qi; Parmeter, Christopher F.; … - In: Journal of Econometrics 184 (2015) 2, pp. 233-241

Estimating gradients is of crucial importance across a broad range of applied economic domains. Here we consider data-driven bandwidth selection based on the gradient of an unknown regression function. This is a difficult problem given that direct observation of the value of the gradient is...

Persistent link: https://www.econbiz.de/10011117420

Flexibility structure and capacity design with human resource considerations

Akşin, Zeynep; Çakan, Nesrin; Karaesmen, Fikri; … - In: Production and operations management : an international … 24 (2015) 7, pp. 1086-1100

Persistent link: https://www.econbiz.de/10011309926

On estimating quantile sensitivities via infinitesimal perturbation analysis

Jiang, Guangxin; Fu, Michael - In: Operations research 63 (2015) 2, pp. 435-441

Persistent link: https://www.econbiz.de/10010526698

Gradient-based smoothing parameter selection for nonparametric regression estimation

Henderson, Daniel J.; Li, Qi; Parmeter, Christopher F.; … - In: Journal of econometrics 184 (2015) 2, pp. 233-241

Persistent link: https://www.econbiz.de/10011339349

Regression models augmented with direct stochastic gradient estimators

Fu, Michael; Qu, Huashuai - In: INFORMS journal on computing : JOC 26 (2014) 3, pp. 484-499

Persistent link: https://www.econbiz.de/10010399808

A basic formula for performance gradient estimation of semi-Markov decision processes

Li, Yanjie; Cao, Fang - In: European Journal of Operational Research 224 (2013) 2, pp. 333-339

This paper presents a basic formula for performance gradient estimation of semi-Markov decision processes (SMDPs) under … formula, we develop three sample-path-based gradient estimation algorithms by using a single sample path. These algorithms … naturally extend many gradient estimation algorithms for discrete-time Markov systems to continuous time semi-Markov models. In …

Persistent link: https://www.econbiz.de/10010588338

A simple method to visualize results in nonlinear regression models

Henderson, Daniel J.; Kumbhakar, Subal C.; Parmeter, … - In: Economics Letters 117 (2012) 3, pp. 578-581

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...

Persistent link: https://www.econbiz.de/10010594106

Gradient Estimation Schemes for Noisy Functions

Brekelmans, Ruud; Den Hertog, Dick; Driessen, L.; … - Tilburg University, Center for Economic Research - 2003

.Good gradient estimation is e.g. important for nonlinear programming solvers.As an error criterion we take the norm of the …

Persistent link: https://www.econbiz.de/10011091661

Conditional Monte Carlo Estimation of Quantile Sensitivities

Fu, Michael C.; Hong, L. Jeff; Hu, Jian-Qiang - In: Management Science 55 (2009) 12, pp. 2019-2027

Estimating quantile sensitivities is important in many optimization applications, from hedging in financial engineering to service-level constraints in inventory control to more general chance constraints in stochastic programming. Recently, Hong (Hong, L. J. 2009. Estimating quantile...

Persistent link: https://www.econbiz.de/10009208830