BaPreStoPro: Bayesian Prediction of Stochastic Processes
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.
Version: |
0.1 |
Depends: |
stats, methods, graphics |
Published: |
2016-06-07 |
Author: |
Simone Hermann |
Maintainer: |
Simone Hermann <hermann at statistik.tu-dortmund.de> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: |
no |
In views: |
Bayesian |
CRAN checks: |
BaPreStoPro results |
Documentation:
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