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r-forge
GeneralizedHyperbolic:The Generalized Hyperbolic Distribution
Functions for the hyperbolic and related distributions. Density, distribution and quantile functions and random number generation are provided for the hyperbolic distribution, the generalized hyperbolic distribution, the generalized inverse Gaussian distribution and the skew-Laplace distribution. Additional functionality is provided for the hyperbolic distribution, normal inverse Gaussian distribution and generalized inverse Gaussian distribution, including fitting of these distributions to data. Linear models with hyperbolic errors may be fitted using hyperblmFit.
Maintained by David Scott. Last updated 10 days ago.
1 stars 8.53 score 124 scripts 27 dependents
cran
fBasics:Rmetrics - Markets and Basic Statistics
Provides a collection of functions to explore and to investigate basic properties of financial returns and related quantities. The covered fields include techniques of explorative data analysis and the investigation of distributional properties, including parameter estimation and hypothesis testing. Even more there are several utility functions for data handling and management.
Maintained by Georgi N. Boshnakov. Last updated 7 months ago.
2 stars 7.19 score 131 dependents
tsmodels
tsdistributions:Location Scale Standardized Distributions
Location-Scale based distributions parameterized in terms of mean, standard deviation, skew and shape parameters and estimation using automatic differentiation. Distributions include the Normal, Student and GED as well as their skewed variants ('Fernandez and Steel'), the 'Johnson SU', and the Generalized Hyperbolic. Also included is the semi-parametric piece wise distribution ('spd') with Pareto tails and kernel interior.
Maintained by Alexios Galanos. Last updated 5 months ago.
distributionsfinanceprobability-distributionprobability-distributionsstatistical-distributionstimeseriescpp
4 stars 6.66 score 19 scripts 2 dependents
ajmcneil
tscopula:Time Series Copula Models
Functions for the analysis of time series using copula models. The package is based on methodology described in the following references. McNeil, A.J. (2021) <doi:10.3390/risks9010014>, Bladt, M., & McNeil, A.J. (2021) <doi:10.1016/j.ecosta.2021.07.004>, Bladt, M., & McNeil, A.J. (2022) <doi:10.1515/demo-2022-0105>.
Maintained by Alexander McNeil. Last updated 1 months ago.
2 stars 5.53 score 12 scripts