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Classical model selection via simulated annealing

Author
BROOKS, S. P1 ; FRIEL, N2 ; KING, R1
[1] University of Cambridge, United Kingdom
[2] University of Glasgow, United Kingdom
Source

Journal of the Royal Statistical Society. Series B, statistical methodology. 2003, Vol 65, pp 503-520, 18 p ; 2 ; ref : 1 p.1/4

ISSN
1369-7412
Scientific domain
Mathematics
Publisher
Blackwell, Oxford
Publication country
United Kingdom
Document type
Article
Language
English
Author keyword
Autoregressive time series Capture-recapture Classical statistics Information criteria Logistic regression Markov chain Monte Carlo methods Optimization Reversible jump Markov chain Monte Carlo sampling Variable selection
Keyword (fr)
Algorithme Analyse donnée Analyse statistique Analyse série temporelle Aspect philosophique Autocorrélation Autorégression Capture Chaîne Markov Critère information Akaike Echantillonnage Enseignement Estimation statistique Fonction vraisemblance Implémentation Loi grand nombre Modèle régression Méthode Monte Carlo Méthode paramétrique Méthode pénalité Méthode statistique Optimisation Problème sélection Processus autorégressif Processus stochastique Rapport vraisemblance Recuit simulé Régression logistique Régression statistique Simulation statistique Statistique rang Série temporelle Test rapport vraisemblance Théorie statistique 62-07 62A01 62F07 62Jxx 62M10 Critère information Estimation paramétrique Méthode sélection Sélection modèle Vraisemblance par paires
Keyword (en)
Algorithm Data analysis Statistical analysis Time series analysis Philosophical aspect Autocorrelation Autoregression Capture Markov chain Akaike information criterion Sampling Teaching Statistical estimation Likelihood function Implementation Law of large numbers Regression model Monte Carlo method Parametric method Penalty method Statistical method Optimization Selection problem Autoregressive processes Stochastic process Likelihood ratio Simulated annealing Logistic regression Statistical regression Statistical simulation Rank statistic Time series Likelihood ratio test Statistical theory Information criterion Selection method Model selection Pairwise likelihood
Keyword (es)
Algoritmo Análisis datos Análisis estadístico Aspecto filosófico Autocorrelación Autoregresión Captura Cadena Markov Criterio información Akaike Muestreo Enseñanza Estimación estadística Función verosimilitud Ejecución Ley gran número Modelo regresión Método Monte Carlo Método paramétrico Método penalidad Método estadístico Optimización Problema selección Proceso estocástico Relación verosimilitud Recocido simulado Regresión logística Regresión estadística Simulación estadística Estadística rango Serie temporal Test razón verosimilitud Teoría estadística
Classification
Pascal
001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02B Mathematical foundations

Pascal
001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02G Parametric inference

Pascal
001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02J Linear inference, regression

Pascal
001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02M Inference from stochastic processes; time series analysis

Discipline
Mathematics
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
14797878

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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