Bayesian estimation and prediction for stochastic processes based on the Euler approximation. Considered processes are: jump diffusion, (mixed) diffusion models, hidden (mixed) diffusion models, non-homogeneous Poisson processes (NHPP), (mixed) regression models for comparison and a regression model including a NHPP.
|Date of publication||2016-06-07 14:28:11|
|Maintainer||Simone Hermann <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.