mdd.mfbvar_ss_iw: Marginal data density method for class 'mfbvar_ss'

In mfbvar: Mixed-Frequency Bayesian VAR Models

Description

Estimate the marginal data density for the model with a steady-state prior.

Usage

## S3 method for class 'mfbvar_ss_iw'
mdd(x, method = 1, ...)

Arguments

x	object of class mfbvar_ss
method	option for which method to choose for computing the mdd (1 or 2)
...	additional arguments (currently only p_trunc for the degree of truncation for method 2 is available)

Details

Two methods for estimating the marginal data density are implemented. Method 1 and 2 correspond to the two methods proposed by Fuentes-Albero and Melosi (2013) and Ankargren, Unosson and Yang (2018).

Value

The logarithm of the marginal data density.

References

Fuentes-Albero, C. and Melosi, L. (2013) Methods for Computing Marginal Data Densities from the Gibbs Output. Journal of Econometrics, 175(2), 132-141, doi: 10.1016/j.jeconom.2013.03.002
Ankargren, S., Unosson, M., & Yang, Y. (2018) A Mixed-Frequency Bayesian Vector Autoregression with a Steady-State Prior. Working Paper, Department of Statistics, Uppsala University No. 2018:3.

See Also

mdd, mdd.mfbvar_minn_iw

mfbvar documentation built on Feb. 10, 2021, 5:12 p.m.