Distributions for Modeling Location, Scale, and Shape - Rigby, Robert A.
- Format: Broché Voir le descriptif
Vous en avez un à vendre ?
Vendez-le-vôtre60,70 €
Occasion · Très Bon État
Ou 15,18 € /mois
Ce vendeur propose la livraison entre 3 et 5 jours
- Livraison GRATUITE
- Livré entre le 27 et le 29 juillet
Livré gratuitement chez vous en 2 semaines. Article presque inutilisé, absence presque totale de traces d'utilisation. 2 millions de ventes réalisées en 5 ans, merci de votre confiance ! Découvrez les avis...
Nos autres offres
-
99,99 €
Occasion · Bon État
Ou 25,00 € /mois
- Livraison : 25,00 €
- Livré entre le 13 et le 18 août
-
140,34 €
Produit Neuf
Ou 35,09 € /mois
- Livraison à 0,01 €
- Livré entre le 31 juillet et le 12 août
Brand new, In English, Fast shipping from London, UK; Tout neuf, en anglais, expédition rapide depuis Londres, Royaume-Uni;ria9781032089423_dbm
Voir le détail de l'annonce
- Payez directement sur Rakuten (CB, PayPal, 4xCB...)
- Récupérez le produit directement chez le vendeur
- Rakuten vous rembourse en cas de problème
Gratuit et sans engagement
Félicitations !
Nous sommes heureux de vous compter parmi nos membres du Club Rakuten !
TROUVER UN MAGASIN
Retour
Avis sur Distributions For Modeling Location, Scale, And Shape de Rigby, Robert A. Format Broché - Livre
0 avis sur Distributions For Modeling Location, Scale, And Shape de Rigby, Robert A. Format Broché - Livre
Les avis publiés font l'objet d'un contrôle automatisé de Rakuten.
Présentation Distributions For Modeling Location, Scale, And Shape de Rigby, Robert A. Format Broché
- Livre
Résumé :
This is the second volume in a series of books about using the GAMLSS R package developed by the authors. This volume presents a broad overview of statistical distributions and how they can be used in practical applications.
Biographie: Robert Rigby was researching in Statistics at London Metropolitan University for over 30 years specializing in distributions and advanced regression and smoothing models (for supervised learning). He is one of the two original developers of GAMLSS models. He is currently a freelance consultant. Mikis Stasinopoulos is a statistician. He has a considerable experience in applied statistics and he is one of the two creators of GAMLSS. He worked as the director of STORM, the statistics and mathematics research centre of London Metropolitan University and now he is working as an independent statistical consultant. Gillian Heller is Professor of Statistics at Macquarie University, Sydney. Her research interests are mainly in flexible regression models for heavy-tailed count data, with applications in biostatistics and insurance. Fernanda De Bastiani is a permanent lecturer in the Statistics Department at Universidade Federal de Pernambuco, Brazil. Her research interests are mainly in flexible regression models, spatial data analysis and influential diagnostics in regression models.
Sommaire:
Part I: Parametric distributions and the GAMLSS family of distributions Chapter 1 Types of distributions Chapter 2 Properties of distributions Chapter 3 The GAMLSS Family of Distributions Chapter 4 Continuous distributions on (?1,1) Chapter 5 Continuous distributions on (0, ?) Chapter 6 Continuous distributions on (0, 1) Chapter 7 Discrete distributions for count data Chapter 8 Binomial type distributions Chapter 9 Mixed distributions Part II: Advanced Topics Chapter 10 Maximum likelihood Chapter 11 Robustness of parameter estimation to outlier Chapter 12 Methods of generating Chapter 13 Discussion of skewness Chapter 14 Discussion of Kurtosis Chapter 15 Skewness and kurtosis comparisons of continuous distributions Chapter 16 Heaviness of tails of continuous Part III: Reference Guide Chapter 17 Continuous distributions on (??,?) Chapter 18 Continuous distributions on (0, ?) Chapter 19 Mixed distributions on 0 to ?, including 0 Chapter 20 Continuous and mixed distributions on [0, 1] Chapter 21 Count data Chapter 22 Count data distributions 23 Binomial type distributions and multinomial distributions
Détails de conformité du produit
Personne responsable dans l'UE