SrasV1, Main, Exploration, bibRecord, 003B66

High-dimension, low-sample size perspectives in constrained statistical inference: The SARSCoV RNA genome in illustration

Identifieur interne : 003B66 ( Main/Exploration ); précédent : 003B65; suivant : 003B67

High-dimension, low-sample size perspectives in constrained statistical inference: The SARSCoV RNA genome in illustration

Auteurs : Pranab K. Sen [États-Unis] ; Ming-Tien Tsai [Taïwan] ; Yuh-Shan Jou [Taïwan]

Source :

Journal of the American Statistical Association [ 0162-1459 ] ; 2007.

RBID : Pascal:07-0300584

Descripteurs français

Pascal (Inist)
- Taille échantillon, Estimation statistique, Donnée catégorielle, Grand échantillon, Epidémie, Distance Hamming, Méthode statistique, Application, 62D05, 62F30.
Wicri :
- topic : Méthode statistique.

English descriptors

KwdEn :
- Application, Categorical data, Epidemic, Hamming distance, Large sample, Sample size, Statistical estimation, Statistical method.

Abstract

High-dimensional categorical data models, often with inadequately large sample sizes, crop up in many fields of application. The SARS epidemic, originating in southern China in 2002, had an identified single-stranded and positive-sense RNA virus with large genome size and moderate mutation rate. The present genomic study is used as a prime illustration for motivating appropriate statistical methodology for comprehending the genomic variation in such high-dimensional categorical data models. Because of underlying restraints, a pseudomarginal approach based on Hamming distance is considered in a constrained statistical inference setup. The union-intersection principle and jackknifing methods are incorporated in exploring appropriate statistical procedures.

Affiliations:

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Le document en format XML

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<front><div type="abstract" xml:lang="en">High-dimensional categorical data models, often with inadequately large sample sizes, crop up in many fields of application. The SARS epidemic, originating in southern China in 2002, had an identified single-stranded and positive-sense RNA virus with large genome size and moderate mutation rate. The present genomic study is used as a prime illustration for motivating appropriate statistical methodology for comprehending the genomic variation in such high-dimensional categorical data models. Because of underlying restraints, a pseudomarginal approach based on Hamming distance is considered in a constrained statistical inference setup. The union-intersection principle and jackknifing methods are incorporated in exploring appropriate statistical procedures.</div>
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High-dimension, low-sample size perspectives in constrained statistical inference: The SARSCoV RNA genome in illustration

High-dimension, low-sample size perspectives in constrained statistical inference: The SARSCoV RNA genome in illustration

Source :

Descripteurs français

English descriptors

Abstract

Links toward previous steps (curation, corpus...)

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri