Statistical analysis high dimensional data (23 résultats)
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Paperback. Etat : new. Paperback. In regression the objective is to determine an appropriate function which reflects reality as accurate as possible but also eliminates irregularities from data noise and is therefore easy to interpret. A popular and flexible approach for estimating the true underlying function is the additive mo…del. One possible approach for fitting additive models is the expansion in B-splines which allows direct calculation of the estimators. If the number of B-splines is too large the estimated functions become wiggly and tend to be very close to the observed data. To avoid this problem of overfitting we use a penalization approach characterized by smoothing parameters. In this thesis we propose the use of genetic algorithms for smoothing parameter optimization. Genetic algorithms are rarely applied in the field of statistics and refer to the principle that better adapted individuals win against their competitors under equal conditions. Apart from smoothing parameter optimization the user often faces datasets containing large numbers of relevant and irrelevant explanatory variables.Appropriate variable selection approaches allow to reduce the number of variables to subsets of relevant variables. We propose to consider the problems of variable selection and choice of smoothing parameters simultaneously by using genetic algorithms. Our approach bases on an appropriate combination of the genetic algorithms for smoothing parameter optimization and variable selection. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Etat : new. Paperback. In regression the objective is to determine an appropriate function which reflects reality as accurate as possible but also eliminates irregularities from data noise and is therefore easy to interpret. A popular and flexible approach for estimating the true underlying function is the additive mo…del. One possible approach for fitting additive models is the expansion in B-splines which allows direct calculation of the estimators. If the number of B-splines is too large the estimated functions become wiggly and tend to be very close to the observed data. To avoid this problem of overfitting we use a penalization approach characterized by smoothing parameters. In this thesis we propose the use of genetic algorithms for smoothing parameter optimization. Genetic algorithms are rarely applied in the field of statistics and refer to the principle that better adapted individuals win against their competitors under equal conditions. Apart from smoothing parameter optimization the user often faces datasets containing large numbers of relevant and irrelevant explanatory variables.Appropriate variable selection approaches allow to reduce the number of variables to subsets of relevant variables. We propose to consider the problems of variable selection and choice of smoothing parameters simultaneously by using genetic algorithms. Our approach bases on an appropriate combination of the genetic algorithms for smoothing parameter optimization and variable selection. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Statistical Analysis for High-Dimensional Data
Frigessi, Arnoldo|Bühlmann, Peter|Glad, Ingrid|Langaas, Mette|Richardson, Sylvia|Vannucci, Marina
Langue : anglais
Edité par Springer International Publishing, 2018
Série : Livre 11 sur 15 - Abel Symposia
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Statistical Analysis for High Dimensional Data
Frigessi, Arnoldo|Bühlmann, Peter|Glad, Ingrid K.|Langaas, Mette|Richardson, Sylvia|Vannucci, Marina
Langue : anglais
Edité par Springer International Publishing, 2016
Série : Livre 11 sur 15 - Abel Symposia
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Etat : New. pp. 318.
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Taschenbuch. Etat : Neu. Statistical Analysis for High-Dimensional Data | The Abel Symposium 2014 | Arnoldo Frigessi (u. a.) | Taschenbuch | Abel Symposia | xii | Englisch | 2018 | Springer | EAN 9783319800738 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]…springer[dot]com | Anbieter: preigu.
Langue : anglais
Edité par Springer International Publishing, Springer International Publishing, 2018
Série : Livre 11 sur 15 - Abel Symposia
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Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvågar, Lofoten, Norway, in May 2014.The focus of the symposium was on statisticaland machine learning methodologies specificall…y developed for inference in 'bigdata' situations, with particular reference to genomic applications. Thecontributors, who are among the most prominent researchers on the theory ofstatistics for high dimensional inference, present new theories and methods, aswell as challenging applications and computational solutions. Specific themesinclude, among others, variable selection and screening, penalised regression,sparsity, thresholding, low dimensional structures, computational challenges,non-convex situations, learning graphical models, sparse covariance andprecision matrices, semi- and non-parametric formulations, multiple testing,classification, factor models, clustering, and preselection.Highlighting cutting-edge researchand casting light on future research directions, the contributions will benefitgraduate students and researchers in computational biology, statistics and themachine learning community.
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Hardcover. Etat : Brand New. 9.25x6.25x0.75 inches. In Stock.
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Hardcover. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Langue : anglais
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Vendeur : liu xing, Nanjing, JS, Chineliu xing
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paperback. Etat : New. Language:Chinese.Paperback. Pub Date: 2025-11 Pages: 270 Publisher: Science Press With the rapid development of science and technology and the rise of generative artificial intelligence. high-dimensional data has become a core challenge in fields such as economic forecasting. precision medicine. and intell…igent manufacturing. High-dimensional statistics deeply integrates the theories and methods of optimization theory. mathematical science. computer science. and information science to extract.
Vendeur : Hakone Books, Fujisawa, KANAG, JaponHakone Books
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This book, published by Asakura Publishing, is an advanced textbook focusing on high-dimensional data analysis. It delves into the sophisticated methods of statistical modeling and model integration, with a particular emphasis on practical application using the R programming language. Ideal for researchers, statisticians, and st…udents, it provides comprehensive coverage within the field of modern statistics. Note: The text is entirely in Japanese. Brand New Japanese Edition. Ships worldwide from Japan via Japan Post. Expedited shipping via FedEx available.
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Etat : new. Questo è un articolo print on demand.
Langue : anglais
Edité par Springer International Publishing Mrz 2018, 2018
Série : Livre 11 sur 15 - Abel Symposia
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvågar, Lofoten, Norway, in May 2014.The focus of the symposium was on statisticaland machine learning methodolo…gies specifically developed for inference in 'bigdata' situations, with particular reference to genomic applications. Thecontributors, who are among the most prominent researchers on the theory ofstatistics for high dimensional inference, present new theories and methods, aswell as challenging applications and computational solutions. Specific themesinclude, among others, variable selection and screening, penalised regression,sparsity, thresholding, low dimensional structures, computational challenges,non-convex situations, learning graphical models, sparse covariance andprecision matrices, semi- and non-parametric formulations, multiple testing,classification, factor models, clustering, and preselection.Highlighting cutting-edge researchand casting light on future research directions, the contributions will benefitgraduate students and researchers in computational biology, statistics and themachine learning community. 320 pp. Englisch.
Langue : anglais
Edité par Springer International Publishing Feb 2016, 2016
Série : Livre 11 sur 15 - Abel Symposia
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvågar, Lofoten, Norway, in May 2014.The focus of the symposium was on statisticaland machine learning methodologies sp…ecifically developed for inference in 'bigdata' situations, with particular reference to genomic applications. Thecontributors, who are among the most prominent researchers on the theory ofstatistics for high dimensional inference, present new theories and methods, aswell as challenging applications and computational solutions. Specific themesinclude, among others, variable selection and screening, penalised regressionsparsity, thresholding, low dimensional structures, computational challengesnon-convex situations, learning graphical models, sparse covariance andprecision matrices, semi- and non-parametric formulations, multiple testingclassification, factor models, clustering, and preselection.Highlighting cutting-edge researchand casting light on future research directions, the contributions will benefitgraduate students and researchers in computational biology, statistics and themachine learning community. 320 pp. Englisch.
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Vendeur : Majestic Books, Hounslow, Royaume-UniMajestic Books
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Etat : New. Print on Demand pp. 318.
Langue : anglais
Edité par Springer, Springer International Publishing Mär 2018, 2018
Série : Livre 11 sur 15 - Abel Symposia
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvågar, Lofoten, Norway, in May 2014.The focus of the symposium was on statisticaland machine learning methodologies… specifically developed for inference in ¿bigdatä situations, with particular reference to genomic applications. Thecontributors, who are among the most prominent researchers on the theory ofstatistics for high dimensional inference, present new theories and methods, aswell as challenging applications and computational solutions. Specific themesinclude, among others, variable selection and screening, penalised regressionsparsity, thresholding, low dimensional structures, computational challengesnon-convex situations, learning graphical models, sparse covariance andprecision matrices, semi- and non-parametric formulations, multiple testingclassification, factor models, clustering, and preselection.Highlighting cutting-edge researchand casting light on future research directions, the contributions will benefitgraduate students and researchers in computational biology, statistics and themachine learning community.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 320 pp. Englisch.
Langue : anglais
Edité par Springer, Palgrave Macmillan Feb 2016, 2016
Série : Livre 11 sur 15 - Abel Symposia
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvågar, Lofoten, Norway, in May 2014.The focus of the symposium was on statisticaland machine learning methodologies specif…ically developed for inference in ¿bigdatä situations, with particular reference to genomic applications. Thecontributors, who are among the most prominent researchers on the theory ofstatistics for high dimensional inference, present new theories and methods, aswell as challenging applications and computational solutions. Specific themesinclude, among others, variable selection and screening, penalised regressionsparsity, thresholding, low dimensional structures, computational challengesnon-convex situations, learning graphical models, sparse covariance andprecision matrices, semi- and non-parametric formulations, multiple testingclassification, factor models, clustering, and preselection.Highlighting cutting-edge researchand casting light on future research directions, the contributions will benefitgraduate students and researchers in computational biology, statistics and themachine learning community.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 320 pp. Englisch.
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Etat : New. PRINT ON DEMAND pp. 318.
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Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvågar, Lofoten, Norway, in May 2014.The focus of the symposium was on statisticaland machine learning methodologies specifi…cally developed for inference in 'bigdata' situations, with particular reference to genomic applications. Thecontributors, who are among the most prominent researchers on the theory ofstatistics for high dimensional inference, present new theories and methods, aswell as challenging applications and computational solutions. Specific themesinclude, among others, variable selection and screening, penalised regression,sparsity, thresholding, low dimensional structures, computational challenges,non-convex situations, learning graphical models, sparse covariance andprecision matrices, semi- and non-parametric formulations, multiple testing,classification, factor models, clustering, and preselection.Highlighting cutting-edge researchand casting light on future research directions, the contributions will benefitgraduate students and researchers in computational biology, statistics and themachine learning community.
