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  • Search: subject:"Integer-valued processes"
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Year of publication
Subject
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Bootstrap inconsistency 3 Count processes 3 Integer-valued processes 3 Mid-distribution function 3 m-out-of-n bootstrap 3 Bootstrap approach 1 Bootstrap-Verfahren 1 Sampling 1 Stichprobenerhebung 1 Theorie 1 Theory 1
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Online availability
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Free 3
Type of publication
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Book / Working Paper 3
Type of publication (narrower categories)
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Working Paper 2 Arbeitspapier 1 Graue Literatur 1 Non-commercial literature 1
Language
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English 2 Undetermined 1
Author
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Jentsch, Carsten 3 Leucht, Anne 3
Institution
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Abteilung für Volkswirtschaftslehre, Universität Mannheim 1
Published in...
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Working Paper Series 1 Working Papers / Abteilung für Volkswirtschaftslehre, Universität Mannheim 1 Working paper series 1
Source
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ECONIS (ZBW) 1 EconStor 1 RePEc 1
Showing 1 - 3 of 3
Cover Image
Bootstrapping sample quantiles of discrete data
Jentsch, Carsten; Leucht, Anne - 2014
Sample quantiles are consistent estimators for the true quantile and satisfy central limit theorems (CLTs) if the underlying distribution is continuous. If the distribution is discrete, the situation is much more delicate. In this case, sample quantiles are known to be not even consistent in...
Persistent link: https://www.econbiz.de/10011490510
Saved in:
Cover Image
Bootstrapping Sample Quantiles of Discrete Data
Jentsch, Carsten; Leucht, Anne - 2014
Sample quantiles are consistent estimators for the true quantile and satisfy central limit theorems (CLTs) if the underlying distribution is continuous. If the distribution is discrete, the situation is much more delicate. In this case, sample quantiles are known to be not even consistent in...
Persistent link: https://www.econbiz.de/10011441851
Saved in:
Cover Image
Bootstrapping Sample Quantiles of Discrete Data
Jentsch, Carsten; Leucht, Anne - Abteilung für Volkswirtschaftslehre, Universität Mannheim - 2014
Sample quantiles are consistent estimators for the true quantile and satisfy central limit theorems (CLTs) if the underlying distribution is continuous. If the distribution is discrete, the situation is much more delicate. In this case, sample quantiles are known to be not even consistent in...
Persistent link: https://www.econbiz.de/10010833246
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