This HTML5 document contains 49 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
dctermshttp://purl.org/dc/terms/
n17http://localhost/temp/predkladatel/
n19http://linked.opendata.cz/resource/domain/vavai/projekt/
n18http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n15http://linked.opendata.cz/ontology/domain/vavai/
n4http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F00216208%3A11320%2F09%3A00206601%21RIV10-GA0-11320___/
n12http://linked.opendata.cz/resource/domain/vavai/zamer/
shttp://schema.org/
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n5http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n16http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n13http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n8http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n14http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n6http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n11http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F09%3A00206601%21RIV10-GA0-11320___
rdf:type
n15:Vysledek skos:Concept
dcterms:description
An R package mixAK is introduced which implements routines for a semiparametric density estimation through normal mixtures using the Markov chain Monte Carlo (MCMC) methodology. Besides producing the MCMC output, the package computes posterior summary statistics for important characteristics of the fitted distribution or computes and visualizes the posterior predictive density. For the estimated models, penalized expected deviance (PED) and deviance information criterion (DIC) is directly computed which allows for a selection of mixture components. Additionally, multivariate right-, left- and interval-censored observations are allowed. For univariate problems, the reversible jump MCMC algorithm has been implemented and can be used for a joint estimation of the mixture parameters and the number of mixture components. We briefly review implemented algorithms and illustrate the use of the package on three real examples of different complexity. An R package mixAK is introduced which implements routines for a semiparametric density estimation through normal mixtures using the Markov chain Monte Carlo (MCMC) methodology. Besides producing the MCMC output, the package computes posterior summary statistics for important characteristics of the fitted distribution or computes and visualizes the posterior predictive density. For the estimated models, penalized expected deviance (PED) and deviance information criterion (DIC) is directly computed which allows for a selection of mixture components. Additionally, multivariate right-, left- and interval-censored observations are allowed. For univariate problems, the reversible jump MCMC algorithm has been implemented and can be used for a joint estimation of the mixture parameters and the number of mixture components. We briefly review implemented algorithms and illustrate the use of the package on three real examples of different complexity.
dcterms:title
A new R package for Bayesian estimation of multivariate normal mixtures allowing for selection of the number of components and interval-censored data A new R package for Bayesian estimation of multivariate normal mixtures allowing for selection of the number of components and interval-censored data
skos:prefLabel
A new R package for Bayesian estimation of multivariate normal mixtures allowing for selection of the number of components and interval-censored data A new R package for Bayesian estimation of multivariate normal mixtures allowing for selection of the number of components and interval-censored data
skos:notation
RIV/00216208:11320/09:00206601!RIV10-GA0-11320___
n3:aktivita
n13:P n13:Z
n3:aktivity
P(GP201/09/P077), Z(MSM0021620839)
n3:cisloPeriodika
12
n3:dodaniDat
n11:2010
n3:domaciTvurceVysledku
n18:8113165
n3:druhVysledku
n6:J
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n4:predkladatel
n3:idSjednocenehoVysledku
301405
n3:idVysledku
RIV/00216208:11320/09:00206601
n3:jazykVysledku
n8:eng
n3:klicovaSlova
package; Bayesian; estimation; multivariate; normal; mixtures; allowing; selection; number; components; interval-censored; data
n3:klicoveSlovo
n5:interval-censored n5:estimation n5:mixtures n5:normal n5:selection n5:package n5:allowing n5:Bayesian n5:multivariate n5:components n5:data n5:number
n3:kodStatuVydavatele
NL - Nizozemsko
n3:kontrolniKodProRIV
[8400DCED426A]
n3:nazevZdroje
Computational Statistics and Data Analysis
n3:obor
n14:BB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:projekt
n19:GP201%2F09%2FP077
n3:rokUplatneniVysledku
n11:2009
n3:svazekPeriodika
53
n3:tvurceVysledku
Komárek, Arnošt
n3:wos
000270624600004
n3:zamer
n12:MSM0021620839
s:issn
0167-9473
s:numberOfPages
16
n17:organizacniJednotka
11320