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SVDNF
View on CRAN: Click
here
Download and install SVDNF package within the R console
Install from CRAN:
install.packages("SVDNF")
Install from Github:
library("remotes")
install_github("cran/SVDNF")
Install by package version:
library("remotes")
install_version("SVDNF", "0.1.11")
Attach the package and use:
library("SVDNF")
Maintained by
Louis Arsenault-Mahjoubi
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.SVDNF . SVDNF results . SVDNF.pdf . SVDNF R package Discrete Nonlinear Filtering for Stochastic Volatility Models . SVDNF_0.1.11.tar.gz . SVDNF_0.1.11.zip . SVDNF_0.1.11.zip . SVDNF_0.1.11.zip . SVDNF_0.1.11.tgz . SVDNF_0.1.11.tgz . SVDNF_0.1.11.tgz . SVDNF_0.1.11.tgz . SVDNF_0.1.11.tgz . SVDNF_0.1.11.tgz . SVDNF archive . https://CRAN.R-project.org/package=SVDNF .
First Published: 2022-10-11
Latest Update: 2023-08-08
Description:
Generates simulated paths from various financial stochastic volatility models with jumps and applies the discrete nonlinear filter (DNF) of Kitagawa (1987) <doi:10.1080/01621459.1987.10478534> to compute likelihood evaluations, filtering distribution estimates, and maximum likelihood parameter estimates. The algorithm is implemented following the work of Bégin and Boudreault (2021) <doi:10.1080/10618600.2020.1840995>.
How to cite:
Louis Arsenault-Mahjoubi (2022). SVDNF: Discrete Nonlinear Filtering for Stochastic Volatility Models. R package version 0.1.11, https://cran.r-project.org/web/packages/SVDNF. Accessed 29 Mar. 2025.
Previous versions and publish date:
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Other R packages that SVDNF depends,
imports, suggests or enhances
Complete documentation for SVDNF
Functions, R codes and Examples using
the SVDNF R package
Some associated functions: DNF.dynamicsSVM . DNFOptim . dynamicsSVM . modelSim.dynamicsSVM . plot.SVDNF .
Some associated R codes: DNF.R . DNFOptim.R . RcppExports.R . dynamicsSVM.R . gridMaker.R . modelSim.R . plot.SVDNF.R . probCalculator.R . Full SVDNF package functions and examples
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