`bmgarch` estimates Bayesian multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) models. `bmgarch` supports ARMA(1,1) and intercept-only (Constant) mean structures, and a variety of MGARCH(P,Q) parameterizations. It also provides forecasts as well as ensemble-forecasts
Bayesian estimation and one-step-ahead forecasting for two-regime TAR model, as well as moni-toring ...
MODEL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (GARCH) PADA DATA RUNTUN WAKTU Oleh ...
textabstractThis note presents the R package bayesGARCH (Ardia, 2007) which provides functions for t...
The development of multivariate generalized autoregressive conditionally heteroscedastic (MGARCH) mo...
We describe the package MSGARCH, which implements Markov-switching GARCH (generalized autoregressive...
We describe the package MSGARCH, which implements Markov-switching GARCH (generalized autoregressive...
Recently, there has been a lot of interest in modelling real data with a heavy-tailed distribution. ...
This master thesis deals with extension of the univariate GARCH model to multivari- ate models. We p...
Recently, there has been a lot of interest in modelling real data with a heavy-tailed distribution. ...
We describe the package MSGARCH, which implements Markov-switching GARCH (generalized autoregressive...
This chapter provides a survey of various multivariate GARCH specifications that model the temporal ...
In empirical work on multivariate financial time series, it is com-mon to postulate a Multivariate G...
The parameters of popular multivariate GARCH (MGARCH) models are restricted so that their estimation...
The R package BGGM provides tools for making Bayesian inference in Gaussian graphical models
This short note provides descriptions about basic usage of the add-on package ccgarch for the free s...
Bayesian estimation and one-step-ahead forecasting for two-regime TAR model, as well as moni-toring ...
MODEL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (GARCH) PADA DATA RUNTUN WAKTU Oleh ...
textabstractThis note presents the R package bayesGARCH (Ardia, 2007) which provides functions for t...
The development of multivariate generalized autoregressive conditionally heteroscedastic (MGARCH) mo...
We describe the package MSGARCH, which implements Markov-switching GARCH (generalized autoregressive...
We describe the package MSGARCH, which implements Markov-switching GARCH (generalized autoregressive...
Recently, there has been a lot of interest in modelling real data with a heavy-tailed distribution. ...
This master thesis deals with extension of the univariate GARCH model to multivari- ate models. We p...
Recently, there has been a lot of interest in modelling real data with a heavy-tailed distribution. ...
We describe the package MSGARCH, which implements Markov-switching GARCH (generalized autoregressive...
This chapter provides a survey of various multivariate GARCH specifications that model the temporal ...
In empirical work on multivariate financial time series, it is com-mon to postulate a Multivariate G...
The parameters of popular multivariate GARCH (MGARCH) models are restricted so that their estimation...
The R package BGGM provides tools for making Bayesian inference in Gaussian graphical models
This short note provides descriptions about basic usage of the add-on package ccgarch for the free s...
Bayesian estimation and one-step-ahead forecasting for two-regime TAR model, as well as moni-toring ...
MODEL GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (GARCH) PADA DATA RUNTUN WAKTU Oleh ...
textabstractThis note presents the R package bayesGARCH (Ardia, 2007) which provides functions for t...
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