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  • Search: subject:"Count processes"
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Year of publication
Subject
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Count processes 4 Bootstrap inconsistency 3 Integer-valued processes 3 Mid-distribution function 3 m-out-of-n bootstrap 3 Theorie 2 Theory 2 Bootstrap approach 1 Bootstrap-Verfahren 1 Business process management 1 Data analysis 1 EM algorithm 1 Markov chain 1 Markov processes 1 Markov-Kette 1 Prozessmanagement 1 Risk analysis 1 Sampling 1 Stichprobenerhebung 1 Stochastic process 1 Stochastischer Prozess 1
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Online availability
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Free 3 Undetermined 1
Type of publication
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Book / Working Paper 3 Article 1
Type of publication (narrower categories)
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Working Paper 2 Arbeitspapier 1 Article in journal 1 Aufsatz in Zeitschrift 1 Graue Literatur 1 Non-commercial literature 1
Language
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English 3 Undetermined 1
Author
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Jentsch, Carsten 3 Leucht, Anne 3 Avanzi, Benjamin 1 Taylor, Greg 1 Wong, Bernard 1 Xian, Alan 1
Institution
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Abteilung für Volkswirtschaftslehre, Universität Mannheim 1
Published in...
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European journal of operational research : EJOR 1 Working Paper Series 1 Working Papers / Abteilung für Volkswirtschaftslehre, Universität Mannheim 1 Working paper series 1
Source
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ECONIS (ZBW) 2 EconStor 1 RePEc 1
Showing 1 - 4 of 4
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Modelling and understanding count processes through a Markov-modulated non-homogeneous Poisson process framework
Avanzi, Benjamin; Taylor, Greg; Wong, Bernard; Xian, Alan - In: European journal of operational research : EJOR 290 (2021) 1, pp. 177-195
Persistent link: https://www.econbiz.de/10012436124
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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
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/10011490510
Saved in:
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