A partir de cette page vous pouvez :
| Retourner au premier écran avec les étagères virtuelles... |
Détail de l'indexation
213 : Statistique non paramétrique
Ouvrages de la bibliothèque en indexation 213
Ajouter le résultat dans votre panier Faire une suggestion Affiner la recherche Interroger des sources externesApplied Nonparametric Statistics in Reliability / M.L. Gámiz / Berlin ; Heidelberg (DEU) ; New York : Springer (2011)
![]()
Titre : Applied Nonparametric Statistics in Reliability Type de document : texte imprimé Auteurs : M.L. Gámiz ; K.B. Kulasekera, ; Nikolaos Limnios, ; Bo H. Lindqvist, Editeur : Berlin ; Heidelberg (DEU) ; New York : Springer Année de publication : 2011 Collection : Springer Series in Reliability Engineering, ISSN 1614-7839 Importance : XIII, 230 p. Présentation : ill. Format : 24 cm ISBN/ISSN/EAN : 978-0-85729-117-2 Note générale : Notes bibliogr. Index
Langues : Anglais (eng) Descripteurs : Contrôle de fiabilité ; Statistique non paramétrique Index. décimale : 213 Statistique non paramétrique Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l'éditeur. En ligne : http://www.springer.com/engineering/production+eng/book/978-0-85729-117-2 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=95132 Applied Nonparametric Statistics in Reliability [texte imprimé] / M.L. Gámiz ; K.B. Kulasekera, ; Nikolaos Limnios, ; Bo H. Lindqvist, . - Springer, 2011 . - XIII, 230 p. : ill. ; 24 cm. - (Springer Series in Reliability Engineering, ISSN 1614-7839) .
ISBN : 978-0-85729-117-2
Notes bibliogr. Index
Langues : Anglais (eng)
Descripteurs : Contrôle de fiabilité ; Statistique non paramétrique Index. décimale : 213 Statistique non paramétrique Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l'éditeur. En ligne : http://www.springer.com/engineering/production+eng/book/978-0-85729-117-2 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=95132 Exemplaires
Code-barres Cote Support Localisation Section Disponibilité I003567 251 GAMI Ouvrage Ensai 2. Statistique Disponible Nonparametric statistical tests / Markus Neuhauser / Boca Raton, Fl. ; Londres : Chapman and Hall/CRC (2011)
![]()
Est accompagné de
Titre : Nonparametric statistical tests : a computational approach Type de document : texte imprimé Auteurs : Markus Neuhauser Editeur : Boca Raton, Fl. ; Londres : Chapman and Hall/CRC Année de publication : 2011 Importance : xvii-229 p. Présentation : tabl., fig. Format : 24 cm ISBN/ISSN/EAN : 978-1-439-86703-7 Note générale : Bibliogr. p. 203. Index Langues : Anglais (eng) Descripteurs : Bootstrap ; Statistique non paramétrique ; Variable discrète Index. décimale : 213 Statistique non paramétrique Résumé : This book describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. It presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. The author considers example data sets in each chapter to illustrate methods. Numerous real-life data from various areas, including the bible, and their analyses provide for greatly diversified reading. [D'après le résumé de l'éditeur] Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l’éditeur.
- Existe aussi en ebook sur la plateforme Dawsonera : ISBN = 978-1-439-86704-4En ligne : http://www.crcpress.com/product/isbn/9781439867037 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=95347 Nonparametric statistical tests : a computational approach [texte imprimé] / Markus Neuhauser . - Boca Raton, Fl. ; Londres : Chapman and Hall/CRC, 2011 . - xvii-229 p. : tabl., fig. ; 24 cm.
ISBN : 978-1-439-86703-7
Bibliogr. p. 203. Index
Langues : Anglais (eng)
Descripteurs : Bootstrap ; Statistique non paramétrique ; Variable discrète Index. décimale : 213 Statistique non paramétrique Résumé : This book describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. It presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. The author considers example data sets in each chapter to illustrate methods. Numerous real-life data from various areas, including the bible, and their analyses provide for greatly diversified reading. [D'après le résumé de l'éditeur] Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l’éditeur.
- Existe aussi en ebook sur la plateforme Dawsonera : ISBN = 978-1-439-86704-4En ligne : http://www.crcpress.com/product/isbn/9781439867037 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=95347
Exemplaires
Code-barres Cote Support Localisation Section Disponibilité E004771 213 NEU Ouvrage de référence ENSAE 2. Statistique Disponible
Accompagne Nonparametric statistical tests / Markus Neuhauser / Boca Raton, Fl. ; Londres : Chapman and Hall/CRC (2011)
Titre : Nonparametric statistical tests : a computational approach Type de document : document électronique Auteurs : Markus Neuhauser Editeur : Londres : Chapman and Hall Année de publication : 2011 Importance : 247 p. ISBN/ISSN/EAN : 978-1-439-86704-4 Langues : Anglais (eng) Descripteurs : Bootstrap ; Statistique non paramétrique ; Variable discrète Index. décimale : 213 Statistique non paramétrique Résumé : Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. The author considers example data sets in each chapter to illustrate methods. Numerous real-life data from various areas, including the bible, and their analyses provide for greatly diversified reading. The book covers: Nonparametric two-sample tests for the location-shift model, specifically the Fisher-Pitman permutation test, the Wilcoxon rank sum test, and the Baumgartner-Weiss-Schindler test Permutation tests, location-scale tests, tests for the nonparametric Behrens-Fisher problem, and tests for a difference in variability Tests for the general alternative, including the (Kolmogorov-)Smirnov test, ordered categorical, and discrete numerical data Well-known one-sample tests such as the sign test and Wilcoxon's signed rank test, a modification suggested by Pratt (1959), a permutation test with original observations, and a one-sample bootstrap test are presented. Tests for more than two groups, the following tests are described in detail: the Kruskal-Wallis test, the permutation F test, the Jonckheere-Terpstra trend test, tests for umbrella alternatives, and the Friedman and Page tests for multiple dependent groups The concepts of independence and correlation, and stratified tests such as the van Elteren test and combination tests The applicability of computer-intensive methods such as bootstrap and permutation tests for non-standard situations and complex designs Although the major development of nonparametric methods came to a certain end in the 1970s, their importance undoubtedly persists. What is still needed is a computer assisted evaluation of their main properties. This book closes that gap. [Résumé de l'éditeur] Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l’éditeur. En ligne : http://www.crcpress.com/product/isbn/9781439867037 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=95845
Accompagne Nonparametric statistical tests / Markus Neuhauser / Boca Raton, Fl. ; Londres : Chapman and Hall/CRC (2011)
Nonparametric statistical tests : a computational approach [document électronique] / Markus Neuhauser . - Londres : Chapman and Hall, 2011 . - 247 p.
ISBN : 978-1-439-86704-4
Langues : Anglais (eng)
Descripteurs : Bootstrap ; Statistique non paramétrique ; Variable discrète Index. décimale : 213 Statistique non paramétrique Résumé : Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. The author considers example data sets in each chapter to illustrate methods. Numerous real-life data from various areas, including the bible, and their analyses provide for greatly diversified reading. The book covers: Nonparametric two-sample tests for the location-shift model, specifically the Fisher-Pitman permutation test, the Wilcoxon rank sum test, and the Baumgartner-Weiss-Schindler test Permutation tests, location-scale tests, tests for the nonparametric Behrens-Fisher problem, and tests for a difference in variability Tests for the general alternative, including the (Kolmogorov-)Smirnov test, ordered categorical, and discrete numerical data Well-known one-sample tests such as the sign test and Wilcoxon's signed rank test, a modification suggested by Pratt (1959), a permutation test with original observations, and a one-sample bootstrap test are presented. Tests for more than two groups, the following tests are described in detail: the Kruskal-Wallis test, the permutation F test, the Jonckheere-Terpstra trend test, tests for umbrella alternatives, and the Friedman and Page tests for multiple dependent groups The concepts of independence and correlation, and stratified tests such as the van Elteren test and combination tests The applicability of computer-intensive methods such as bootstrap and permutation tests for non-standard situations and complex designs Although the major development of nonparametric methods came to a certain end in the 1970s, their importance undoubtedly persists. What is still needed is a computer assisted evaluation of their main properties. This book closes that gap. [Résumé de l'éditeur] Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l’éditeur. En ligne : http://www.crcpress.com/product/isbn/9781439867037 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=95845 Est accompagné de
Titre : Smoothing Splines : Methods and Applications Type de document : texte imprimé Auteurs : Yuedong Wang Mention d'édition : 1 Editeur : Boca Raton, Fl. ; Londres : Chapman and Hall/CRC Année de publication : 2011 Collection : Chapman & Hall/CRC Monographs on statistics & applied probability, ISSN 0960-6696 Importance : xxiv, 370 p. Présentation : fig. Format : 24 cm ISBN/ISSN/EAN : 978-1-420-07755-1 Note générale : Bibliogr. p. 347. Index Langues : Anglais (eng) Descripteurs : Régression ; Régression polynomiale ; Statistique non paramétrique Index. décimale : 213 Statistique non paramétrique Résumé : This book covers basic smoothing spline models, including polynomial, periodic, spherical, thin-plate, L-, and partial splines, as well as more advanced models, such as smoothing spline ANOVA, extended and generalized smoothing spline ANOVA, vector spline, nonparametric nonlinear regression, semiparametric regression, and semiparametric mixed-effects models. It also presents methods for model selection and inference. It provides unified frameworks for estimation, inference, and software implementation by using the general forms of nonparametric/semiparametric, linear/nonlinear, and fixed/mixed smoothing spline models. The theory of reproducing kernel Hilbert space (RKHS) is used to present various smoothing spline models in a unified fashion. Although this approach can be technical and difficult, the author makes the advanced smoothing spline methodology based on RKHS accessible to practitioners and students. He offers a gentle introduction to RKHS, keeps theory at a minimum level, and explains how RKHS can be used to construct spline models. It also offers a balanced mix of methodology, computation, implementation, software, and applications. It uses R to perform all data analyses and includes a host of real data examples from astronomy, economics, medicine, and meteorology. The codes for all examples, along with related developments, can be found on the book's web page. [Résumé de l'éditeur] Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l’éditeur
- Existe aussi en ebook sur la plateforme Dawsonera : ISBN = 978-1-420-07756-8En ligne : http://www.crcpress.com/product/isbn/9781420077551 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=93255 Smoothing Splines : Methods and Applications [texte imprimé] / Yuedong Wang . - 1 . - Chapman and Hall/CRC, 2011 . - xxiv, 370 p. : fig. ; 24 cm. - (Chapman & Hall/CRC Monographs on statistics & applied probability, ISSN 0960-6696) .
ISBN : 978-1-420-07755-1
Bibliogr. p. 347. Index
Langues : Anglais (eng)
Descripteurs : Régression ; Régression polynomiale ; Statistique non paramétrique Index. décimale : 213 Statistique non paramétrique Résumé : This book covers basic smoothing spline models, including polynomial, periodic, spherical, thin-plate, L-, and partial splines, as well as more advanced models, such as smoothing spline ANOVA, extended and generalized smoothing spline ANOVA, vector spline, nonparametric nonlinear regression, semiparametric regression, and semiparametric mixed-effects models. It also presents methods for model selection and inference. It provides unified frameworks for estimation, inference, and software implementation by using the general forms of nonparametric/semiparametric, linear/nonlinear, and fixed/mixed smoothing spline models. The theory of reproducing kernel Hilbert space (RKHS) is used to present various smoothing spline models in a unified fashion. Although this approach can be technical and difficult, the author makes the advanced smoothing spline methodology based on RKHS accessible to practitioners and students. He offers a gentle introduction to RKHS, keeps theory at a minimum level, and explains how RKHS can be used to construct spline models. It also offers a balanced mix of methodology, computation, implementation, software, and applications. It uses R to perform all data analyses and includes a host of real data examples from astronomy, economics, medicine, and meteorology. The codes for all examples, along with related developments, can be found on the book's web page. [Résumé de l'éditeur] Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l’éditeur
- Existe aussi en ebook sur la plateforme Dawsonera : ISBN = 978-1-420-07756-8En ligne : http://www.crcpress.com/product/isbn/9781420077551 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=93255
Exemplaires
Code-barres Cote Support Localisation Section Disponibilité E004768 213 WAN Ouvrage de référence ENSAE 2. Statistique Disponible
Accompagne Smoothing Splines / Yuedong Wang / Boca Raton, Fl. ; Londres : Chapman and Hall/CRC (2011)
Titre : Smoothing Splines : Methods and Applications Type de document : document électronique Auteurs : Yuedong Wang, Auteur Mention d'édition : 1 Editeur : Boca Raton, Fl. ; Londres : Chapman and Hall/CRC Année de publication : 2011 Collection : Chapman & Hall/CRC Monographs on statistics & applied probability, ISSN 0960-6696 Importance : 380 p. ISBN/ISSN/EAN : 978-1-420-07756-8 Langues : Anglais (eng) Descripteurs : Régression ; Régression polynomiale ; Statistique non paramétrique Index. décimale : 213 Statistique non paramétrique Résumé : This book covers basic smoothing spline models, including polynomial, periodic, spherical, thin-plate, L-, and partial splines, as well as more advanced models, such as smoothing spline ANOVA, extended and generalized smoothing spline ANOVA, vector spline, nonparametric nonlinear regression, semiparametric regression, and semiparametric mixed-effects models. It also presents methods for model selection and inference. It provides unified frameworks for estimation, inference, and software implementation by using the general forms of nonparametric/semiparametric, linear/nonlinear, and fixed/mixed smoothing spline models. The theory of reproducing kernel Hilbert space (RKHS) is used to present various smoothing spline models in a unified fashion. Although this approach can be technical and difficult, the author makes the advanced smoothing spline methodology based on RKHS accessible to practitioners and students. He offers a gentle introduction to RKHS, keeps theory at a minimum level, and explains how RKHS can be used to construct spline models. It also offers a balanced mix of methodology, computation, implementation, software, and applications. It uses R to perform all data analyses and includes a host of real data examples from astronomy, economics, medicine, and meteorology. The codes for all examples, along with related developments, can be found on the book's web page. [Résumé de l'éditeur] Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l’éditeur. . En ligne : http://www.crcpress.com/product/isbn/9781420077551 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=95846
Accompagne Smoothing Splines / Yuedong Wang / Boca Raton, Fl. ; Londres : Chapman and Hall/CRC (2011)
Smoothing Splines : Methods and Applications [document électronique] / Yuedong Wang, Auteur . - 1 . - Chapman and Hall/CRC, 2011 . - 380 p.. - (Chapman & Hall/CRC Monographs on statistics & applied probability, ISSN 0960-6696) .
ISBN : 978-1-420-07756-8
Langues : Anglais (eng)
Descripteurs : Régression ; Régression polynomiale ; Statistique non paramétrique Index. décimale : 213 Statistique non paramétrique Résumé : This book covers basic smoothing spline models, including polynomial, periodic, spherical, thin-plate, L-, and partial splines, as well as more advanced models, such as smoothing spline ANOVA, extended and generalized smoothing spline ANOVA, vector spline, nonparametric nonlinear regression, semiparametric regression, and semiparametric mixed-effects models. It also presents methods for model selection and inference. It provides unified frameworks for estimation, inference, and software implementation by using the general forms of nonparametric/semiparametric, linear/nonlinear, and fixed/mixed smoothing spline models. The theory of reproducing kernel Hilbert space (RKHS) is used to present various smoothing spline models in a unified fashion. Although this approach can be technical and difficult, the author makes the advanced smoothing spline methodology based on RKHS accessible to practitioners and students. He offers a gentle introduction to RKHS, keeps theory at a minimum level, and explains how RKHS can be used to construct spline models. It also offers a balanced mix of methodology, computation, implementation, software, and applications. It uses R to perform all data analyses and includes a host of real data examples from astronomy, economics, medicine, and meteorology. The codes for all examples, along with related developments, can be found on the book's web page. [Résumé de l'éditeur] Note de contenu : Voir résumé et/ou sommaire détaillé en ligne sur le site de l’éditeur. . En ligne : http://www.crcpress.com/product/isbn/9781420077551 Permalink : http://genes.bibli.fr/opac/index.php?lvl=notice_display&id=95846 Estimation non-paramétrique pour des processus de diffusion / Arnak Dalalyan / Sarrebruck : Editions Universitaires Europeennes (2010)
![]()
PermalinkNonparametric Inference on Manifolds / Abhishek Bhattacharya / Cambridge (GBR) ; West Nyack, N.Y. : CUP. Cambridge University Press (2010)
![]()
PermalinkNonparametric Statistical Inference / Jean Dickinson Gibbons ; Subhabrata Chakraborti / Boca Raton, Fl. ; Londres : Chapman and Hall/CRC (2010)
![]()
PermalinkRobust Nonparametric Statistical Methods / Thomas P. Hettmansperger ; Joseph W. McKean / Boca Raton, Fl. ; Londres : Chapman and Hall/CRC (2010)
![]()
PermalinkMaximum penalized likelihood estimation. Vol. II. Regression / Eggermont, Paul P. / Berlin ; Heidelberg (DEU) ; New York : Springer (2009)
![]()
PermalinkNonparametric estimation for renewal and Markov processes / Odile Pons / Odile Pons (2009)
PermalinkIntroduction to nonparametric estimation / Alexandre B. Tsybakov / Berlin ; Heidelberg (DEU) ; New York : Springer (2008)
![]()
PermalinkApplied nonparametric statistical methods / Peter Sprent / Boca Raton, Fl. ; Londres : Chapman and Hall/CRC (2007)
PermalinkEstimation et classification non paramétriques par la méthode du noyau sur les champs aléatoires mélangeants / Ahmad Younso / Montpellier : Université de Montpellier II (2007)
PermalinkIdentification and estimation of incentive problems / Xavier d' Haultfoeuille / Paris : INSEE-CREST (2007)
![]()
PermalinkInférence statistique par des transformées de Fourier pour des modèles de régression semi-paramétriques / Myriam Vimond / Toulouse : Université Toulouse III - Paul Sabatier (2007)
![]()
PermalinkLectures on empirical process / Eustasio del Barrio / Zürich : EMS. European Mathematical Society (2007)
![]()
PermalinkPermalinkModèles semi-paramétriques appliqués à la prévision des séries temporelles / Vincent Lefieux / Rennes : Université Rennes 2 (2007)
![]()
![]()
PermalinkNonparametric analysis of univariate heavy-tailed data / Natalia Markovich / Chichester (GBR) ; Hoboken, N.J. : John Wiley & Sons (2007)
![]()
Permalink








