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
CRAN checks: BaPreStoPro results

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Reference manual: BaPreStoPro.pdf
Package source: BaPreStoPro_0.1.tar.gz
Windows binaries: r-devel: BaPreStoPro_0.1.zip, r-release: BaPreStoPro_0.1.zip, r-oldrel: BaPreStoPro_0.1.zip
OS X El Capitan binaries: r-release: BaPreStoPro_0.1.tgz
OS X Mavericks binaries: r-oldrel: BaPreStoPro_0.1.tgz

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