Package: invgamstochvol 1.0.0

Blessings Majoni

invgamstochvol: Obtains the Log Likelihood for an Inverse Gamma Stochastic Volatility Model

Computes the log likelihood for an inverse gamma stochastic volatility model using a closed form expression of the likelihood. The details of the computation of this closed form expression are given in Gonzalez and Majoni (2023) <http://rcea.org/RePEc/pdf/wp23-11.pdf> . The closed form expression is obtained for a stationary inverse gamma stochastic volatility model by marginalising out the volatility. This allows the user to obtain the maximum likelihood estimator for this non linear non Gaussian state space model. In addition, the user can obtain the estimates of the smoothed volatility using the exact smoothing distributions.

Authors:Leon Gonzalez [aut, cph], Blessings Majoni [aut, cre]

invgamstochvol_1.0.0.tar.gz
invgamstochvol_1.0.0.tar.gz(r-4.7-arm64)invgamstochvol_1.0.0.tar.gz(r-4.7-x86_64)invgamstochvol_1.0.0.tar.gz(r-4.6-arm64)invgamstochvol_1.0.0.tar.gz(r-4.6-x86_64)
invgamstochvol_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
invgamstochvol/json (API)
NEWS

# Install 'invgamstochvol' in R:
install.packages('invgamstochvol', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • US_Inf_Data - Data to use in the invgamstochvol package

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cppopenmp

2.00 score 3 scripts 135 downloads 3 exports 2 dependencies

Last updated from:387c716290. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK115
linux-devel-x86_64OK119
source / vignettesOK189
linux-release-arm64OK112
linux-release-x86_64OK118
wasm-releaseOK121

Exports:DrawK0lik_cloourgeo

Dependencies:RcppRcppArmadillo

A Tutorial for invgamstochvol package

Rendered frominvgamstochvol.Rmdusingknitr::rmarkdownon Jun 07 2026.

Last update: 2023-08-10
Started: 2023-08-10