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Using a bootstrap method to choose the sample fraction in tail index estimation
Danielsson, J.; de Haan, de Haan, L.F.M.; Peng, Peng, L.; … - Faculteit der Economische Wetenschappen, Erasmus … - 2000
a two step subsample bootstrap method. This method adaptively determines the sample fraction that minimizes the …
Persistent link: https://www.econbiz.de/10010837770
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Using a bootstrap method to choose the sample fraction in tail index estimation
Danielsson, J.; Haan, L.F.M. de; Peng, L.; Vries, C.G. de - Erasmus University Rotterdam, Econometric Institute - 2000
a two step subsample bootstrap method. This method adaptively determines the sample fraction that minimizes the …
Persistent link: https://www.econbiz.de/10008484074
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A bootstrap-based method to achieve optimality in estimating the extreme-value index
Haan, Laurens de; Peng, Liang; Pereira, T. Themido - 1997
Estimators of the extreme-value index are based on a set of upper order statistics. We present an adaptivemethod to choose the number of order statistics involved in an optimal way, balancing variance and biascomponents. Recently this has been achieved for the similar but somewhat less involved...
Persistent link: https://www.econbiz.de/10010342310
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Bootstrapping standard errors of estimates based on structural time series models
Krieg, Sabine; Brakel, Jan A. van den - 2017
Persistent link: https://www.econbiz.de/10011762439
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A bootstrap-based method to achieve optimality on estimating the extreme-value index
Draisma, Draisma, G.; de Haan, de Haan, L.F.M.; Peng, … - Faculteit der Economische Wetenschappen, Erasmus … - 2000
choose the number of order statistics involved in an optimal way, balancing variance and bias components. Recently this has …
Persistent link: https://www.econbiz.de/10010837846
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A bootstrap-based method to achieve optimality on estimating the extreme-value index
Draisma, G.; Haan, L.F.M. de; Peng, L.; Pereira, T.T. - Erasmus University Rotterdam, Econometric Institute - 2000
choose the number of order statistics involved in an optimal way, balancing variance and bias components. Recently this has …
Persistent link: https://www.econbiz.de/10008484088
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Minimisation of bias of Pearson correlation coefficient in presence of coincidental outliers
Tsagkanos, Athanasios - In: International journal of computational economics and … 8 (2018) 1, pp. 121-128
Persistent link: https://www.econbiz.de/10011990367
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A simplified approach to bias estimation for correlations
Liu, Xiaofeng Steven - In: Epidemiologic Methods 10 (2021) 1
Abstract Objectives We introduce a simple and unified methodology to estimate the bias of Pearson correlation …
Persistent link: https://www.econbiz.de/10014590691
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Bias correction in the dynamic panel data model with a nonscalar disturbance covariance matrix
Bun, Maurice J. G. - 2001
Approximation formulae are developed for the bias of ordinary andgeneralized Least Squares Dummy Variable (LSDV … proper modelling of thedisturbance covariance structure is indispensable. The biasapproximations are used to construct bias … plausible long-run effects are obtained by the biascorrected estimators. Moreover, bias correction can be substantialunderlining …
Persistent link: https://www.econbiz.de/10011313930
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Bias-correction in vector autoregressive models : a simulation study
Engsted, Tom; Pedersen, Thomas Q. - In: Econometrics : open access journal 2 (2014) 1, pp. 45-71
compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models …We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non …-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact …
Persistent link: https://www.econbiz.de/10010336196