Bayesian Essentials with R
This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian...
| Κύριοι συγγραφείς: | Marin, Jean-Michel (Συγγραφέας), Robert, Christian P. (Συγγραφέας) |
|---|---|
| Συγγραφή απο Οργανισμό/Αρχή: | SpringerLink (Online service) |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
New York, NY :
Springer New York : Imprint: Springer,
2014.
|
| Έκδοση: | 2nd ed. 2014. |
| Σειρά: | Springer Texts in Statistics,
|
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Παρόμοια τεκμήρια
-
Bayesian Networks in R with Applications in Systems Biology /
ανά: Nagarajan, Radhakrishnan, κ.ά.
Έκδοση: (2013) -
Bayesian Nonparametric Data Analysis
ανά: Müller, Peter, κ.ά.
Έκδοση: (2015) -
Essential Statistical Inference Theory and Methods /
ανά: Boos, Dennis D., κ.ά.
Έκδοση: (2013) -
Examples in Parametric Inference with R
ανά: Dixit, Ulhas Jayram
Έκδοση: (2016) -
Introduction to Probability Simulation and Gibbs Sampling with R
ανά: Suess, Eric A., κ.ά.
Έκδοση: (2010)