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ghyp: Generalized Hyperbolic Distribution and Its Special Cases

Detailed functionality for working with the univariate and multivariate Generalized Hyperbolic distribution and its special cases (Hyperbolic (hyp), Normal Inverse Gaussian (NIG), Variance Gamma (VG), skewed Student-t and Gaussian distribution). Especially, it contains fitting procedures, an AIC-based model selection routine, and functions for the computation of density, quantile, probability, random variates, expected shortfall and some portfolio optimization and plotting routines as well as the likelihood ratio test. In addition, it contains the Generalized Inverse Gaussian distribution. See Chapter 3 of A. J. McNeil, R. Frey, and P. Embrechts. Quantitative risk management: Concepts, techniques and tools. Princeton University Press, Princeton (2005).

Version: 1.6.5
Depends: R (≥ 2.7), methods, numDeriv, graphics, stats, MASS
Published: 2024-08-26
DOI: 10.32614/CRAN.package.ghyp
Author: Marc Weibel [aut, cre], David Luethi [aut], Henriette-Elise Breymann [aut]
Maintainer: Marc Weibel <marc.weibel at quantsulting.ch>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README ChangeLog
In views: Distributions, Finance
CRAN checks: ghyp results

Documentation:

Reference manual: ghyp.pdf
Vignettes: Generalized Hyperbolic Distribution (source, R code)

Downloads:

Package source: ghyp_1.6.5.tar.gz
Windows binaries: r-devel: ghyp_1.6.5.zip, r-release: ghyp_1.6.5.zip, r-oldrel: ghyp_1.6.5.zip
macOS binaries: r-release (arm64): ghyp_1.6.5.tgz, r-oldrel (arm64): ghyp_1.6.5.tgz, r-release (x86_64): ghyp_1.6.5.tgz, r-oldrel (x86_64): ghyp_1.6.5.tgz
Old sources: ghyp archive

Reverse dependencies:

Reverse depends: sharpeRratio
Reverse imports: fitHeavyTail, MixGHD, StockDistFit, yuimaGUI
Reverse suggests: ffp

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ghyp to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.