Fitting a parametric skewed t distribution of Fernandez and Steel's (1998) method
Usage
skew_t_fun(data, gridpoints, M = 5001)
Value
m
Grid points within data range
skewed_t_den_fore
Density forecasts via a skewed t distribution
Arguments
data
a data matrix of dimension n by p
gridpoints
Grid points
M
number of grid points
Author
Han Lin Shang
Details
1) Fit a skewed t distribution to data, and obtain four latent parameters;
2) Transform the four latent parameters so that they are un-constrained;
3) Fit a vector autoregressive model to these transformed latent parameters;
4) Obtain their forecasts, and then back-transform them to the original scales;
5) Via the skewed t distribution in Step 1), we obtain forecast density using the forecast latent parameters.
References
Fernandez, C. and Steel, M. F. J. (1998), `On Bayesian modeling of fat tails and skewness', Journal of the American Statistical Association: Theory and Methods, 93(441), 359-371.