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Parameter learning and change detection using a particle filter with accelerated adaptation

Gellert, Karol; Schlögl, Erik - In: Risks : open access journal 9 (2021) 12, pp. 1-18

shifts and stochastic volatility. The filter adapts to regime shifts extremely rapidly and delivers a clear heuristic for … distinguishing between regime shifts and stochastic volatility, even though the model dynamics assumed by the filter exhibit neither …

Persistent link: https://www.econbiz.de/10012794245

Bootstrapping confidence intervals for linear programming efficiency scores : with an illustration using Italian banking data

Ferrier, Gary Donald; Hirschberg, Joseph G. - 1995

Persistent link: https://www.econbiz.de/10000923034

Measuring technical and scale ineffeciencies in the beer industry : nonparametric and parametric evidence

Elyasiani, Elyas - In: The quarterly review of economics and finance : journal … 33 (1993) 4, pp. 383-408

Persistent link: https://www.econbiz.de/10001157871

Bootstrapping confidence intervals for linear programming efficiency scores : with an illustration using Italian banking data

Ferrier, Gary Donald - In: Journal of productivity analysis 8 (1997) 1, pp. 19-33

Persistent link: https://www.econbiz.de/10001218630

Oriented models: ranking comparison to stochastic frontier approach

Brázdik, František - 2005

Persistent link: https://www.econbiz.de/10003094429

Average-profit efficiency and optimal scale sizes with integer data and undesirable outputs

Omshi, Somayye Karimi; Kordrostami, Sohrab; … - In: Journal of economic studies 50 (2023) 7, pp. 1549-1569

Persistent link: https://www.econbiz.de/10014428613

Evaluating NBA player performance using bounded integer data envelopment analysis

Chen, Ya; Gong, Yande; Li, Xiang - In: INFOR : information systems and operational research 55 (2017) 1, pp. 38-51

Persistent link: https://www.econbiz.de/10011779722

Oriented Stochastic Data Envelopment Models : Ranking Comparison to Stochastic Frontier Approach

Brázdik, František - 2005

Results of data envelopment analysis sensitively respond to stochastic noise in the data. In this paper, by introduction of output augmentation and input reduction I extend additive models for stochastic data envelopment analysis (SDEA), which were developed by Li (1998) to handle the noise in...

Persistent link: https://www.econbiz.de/10014060477

Stochastic data envelopment analysis : a quantile regression approach to estimate the production frontier

Jradi, Samah; Ruggiero, John - In: European journal of operational research : EJOR 278 (2019) 2, pp. 385-393

Persistent link: https://www.econbiz.de/10012102540

New efficiency theory : with applications of data envelopment analysis

Sengupta, Jati K. - 2003

Persistent link: https://www.econbiz.de/10014006772