Statistical Inference for Discrete Time Stochastic Processes
This work is an overview of statistical inference in stationary, discrete time stochastic processes. Results in the last fifteen years, particularly on non-Gaussian sequences and semi-parametric and non-parametric analysis have been reviewed. The first chapter gives a background of results on marti...
Guardat en:
| Autor principal: | |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
New Delhi :
Springer India
[20..].
Cham : Springer Nature |
| Edició: | 1st ed. 2013. |
| Col·lecció: | SpringerBriefs in Statistics
|
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Statistical Inference for Discrete Time Stochastic Processes, Texte imprimé, 9788132207627 • Statistical Inference for Discrete Time Stochastic Processes, Texte imprimé, 9788132207641 |
Taula de continguts:
- CAN Estimators from dependent observations Markov chains and their extensions Non-Gaussian ARMA models Estimating Functions Estimation of joint densities and conditional expectation Bootstrap and other resampling procedures Index