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stochvolTMB  

Likelihood Estimation of Stochastic Volatility Models
View on CRAN: Click here


Download and install stochvolTMB package within the R console
Install from CRAN:
install.packages("stochvolTMB")

Install from Github:
library("remotes")
install_github("cran/stochvolTMB")

Install by package version:
library("remotes")
install_version("stochvolTMB", "0.2.0")



Attach the package and use:
library("stochvolTMB")
Maintained by
Jens Christian Wahl
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-02
Latest Update: 2021-08-13
Description:
Parameter estimation for stochastic volatility models using maximum likelihood. The latent log-volatility is integrated out of the likelihood using the Laplace approximation. The models are fitted via 'TMB' (Template Model Builder) (Kristensen, Nielsen, Berg, Skaug, and Bell (2016) <doi:10.18637/jss.v070.i05>).
How to cite:
Jens Christian Wahl (2020). stochvolTMB: Likelihood Estimation of Stochastic Volatility Models. R package version 0.2.0, https://cran.r-project.org/web/packages/stochvolTMB
Previous versions and publish date:
0.1.0 (2020-09-02 11:00), 0.1.1 (2020-09-02 14:30), 0.1.2 (2020-09-04 14:10)
Other packages that cited stochvolTMB R package
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Other R packages that stochvolTMB depends, imports, suggests or enhances
Functions, R codes and Examples using the stochvolTMB R package
Some associated functions: demo . estimate_parameters . get_nll . logit . plot.stochvolTMB . plot_forecast . predict.stochvolTMB . residuals . sim_sv . simulate_parameters . spy . summary . summary.stochvolTMB_predict . 
Some associated R codes: data.R . demo.R . optSV.R . residuals.R . simSV.R . stochvolTMB-package.R . volplot.R . zzz.R .  Full stochvolTMB package functions and examples
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