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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.
Getting started
Browse package contents
Package details |
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| Author | Simone Hermann |
| Maintainer | Simone Hermann <hermann@statistik.tu-dortmund.de> |
| License | GPL (>= 2) |
| Version | 0.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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