Smoothing spline ANOVA models
Nonparametric function estimation with stochastic data, otherwiseknown as smoothing, has been studied by several generations ofstatisticians. Assisted by the ample computing power in today'sservers, desktops, and laptops, smoothing methods have been findingtheir ways into everyday data analysis...
Enregistré dans:
| Auteur principal: | |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Édition: | 2nd ed. 2013. |
| Collection: | Springer Series in Statistics
297 |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Smoothing spline ANOVA models, Chong Gu, 2nd ed., New York, Springer, 2013, 1 vol. (XVIII-433 p.), Springer series in statistics, 978-1-4614-5368-0 • Smoothing Spline ANOVA Models, Texte imprimé, 9781489989840 • Smoothing Spline ANOVA Models, Texte imprimé, 9781461453703 |
Table des matières:
- Introduction Model Construction Regression with Gaussian-Type Responses More Splines Regression and Exponential Families Regression with Correlated Responses Probability Density Estimation Hazard Rate Estimation Asymptotic Convergence Penalized Pseudo Likelihood