bayesVAR_TVP: Estimates TVP-VAR model using MCMC sampler.

Description Usage Arguments Value References

View source: R/bayesVAR_tvp.R

Description

Estimates Time-Varying Parameters VAR model using MCMC sampler.

Y_t = Z_t β_t + ε_t; ε_t ~ N(0, H)

β_t = β_{t-1} + u_t; u_t ~ N(0, Q)

Prior parameters are estimated using OLS method on training sample.

Usage

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bayesVAR_TVP(Y, p = 1, nburn = 10000, nsim = 50000, tau = 40,
  beta.algorithm = "DK", reject.explosive = FALSE)

Arguments

Y

Matrix or timeseries object

p

Integer for the lag order (default is p=1)

nburn

Number of MCMC draws used to initialize the sampler (defaults to 10000)

nsim

Number of MCMC draws excluding burn-in (defaults to 50000)

tau

Length of training sample used for determining prior parameters via OLS

beta.algorithm

Algorithm for drawing time-varying VAR parameters. Either 'DK' for Durbin and Coopman 2002, or 'CC' for Carter and Cohn 1994. Defaults to 'DK'

reject.explosive

Should the explosive (not stable) draws of VAR parameters be rejected? Defaults to 'FALSE'. For rationale consult Cogley and Sargent 2005. May significantly increase computtion time!

Value

beta

Draws of time-varying parameters (beta_t). 4D array [t x M x M*p+1 x draw]

H

Draws of observation equation error term covariance matrix H. 3D array [M x M x draw]

Q

Draws of state equation error term covariance matrix Q. 3D array [M x M x draw]

References


GediminasB/bayesVAR_TVP documentation built on Jan. 23, 2018, 8:11 a.m.