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  • Search: subject:"Bayesian predictive inference"
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Year of publication
Subject
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Bayesian predictive inference 3 Central limit theorem 3 Conditional identity in distribution 3 Empirical distribution 3 Exchangeability 3 Predictive distribution 3 Stable convergence 3 Estimation theory 1 Forecasting model 1 Probability theory 1 Prognoseverfahren 1 Schätztheorie 1 Statistical distribution 1 Statistische Verteilung 1 Wahrscheinlichkeitsrechnung 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 3
Author
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Berti, Patrizia 3 Crimaldi, Irene 3 Pratelli, Luca 3 Rigo, Pietro 3
Institution
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Dipartimento di Scienze Economiche e Aziendali, Università degli Studi di Pavia 1
Published in...
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Quaderni di Dipartimento 2 Quaderni del Dipartimento 1
Source
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ECONIS (ZBW) 1 EconStor 1 RePEc 1
Showing 1 - 3 of 3
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Rate of Convergence of Predictive Distributions for Dependent Data
Berti, Patrizia; Crimaldi, Irene; Pratelli, Luca; Rigo, … - 2009
This paper deals with empirical processes of the type Cn(B) = n^(1/2) {µn(B) - P(Xn+1 in B
Persistent link: https://www.econbiz.de/10010335326
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Cover Image
Rate of Convergence of Predictive Distributions for Dependent Data
Berti, Patrizia; Crimaldi, Irene; Pratelli, Luca; Rigo, … - Dipartimento di Scienze Economiche e Aziendali, … - 2009
This paper deals with empirical processes of the type Cn(B) = n^(1/2) {µn(B) - P(Xn+1 in B | X1, . . . ,Xn)} , where (Xn) is a sequence of random variables and µn = (1/n)SUM(i=1,..,n) d(Xi) the empirical measure. Conditions for supB|Cn(B)| to converge stably (in particular, in distribution)...
Persistent link: https://www.econbiz.de/10009651795
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Cover Image
Rate of convergence of predictive distributions for dependent data
Berti, Patrizia; Crimaldi, Irene; Pratelli, Luca; Rigo, … - 2009
This paper deals with empirical processes of the type Cn(B) = n^(1/2) {µn(B) - P(Xn+1 in B | X1, . . . ,Xn)} , where (Xn) is a sequence of random variables and µn = (1/n)SUM(i=1,..,n) d(Xi) the empirical measure. Conditions for supB|Cn(B)| to converge stably (in particular, in distribution)...
Persistent link: https://www.econbiz.de/10010259915
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