Compute one draw of the threshold parameter in th TAR(1) model with Gaussian innovations and time-dependent innovation variances. The sampler utilizes metropolis hasting to draw from uniform prior.
t_sampleR_mh(
h_yc,
h_phi,
h_phi2,
h_sigma_eta_t,
h_sigma_eta_0,
h_st,
h_r,
lower_b,
upper_b,
omega,
D
)the sampled threshold value r
the T vector of centered log-volatilities
(i.e., the log-vols minus the unconditional means dhs_mean)
the 1 vector of previous AR(1) coefficient(s)
the 1 vector of previous penalty coefficient(s)
the T vector of log-vol innovation standard deviations
the 1 vector of initial log-vol innovation standard deviations
the T vector of indicators on whether each time-step exceed the estimated threshold
1 the previous draw of the threshold parameter
the lower bound in the uniform prior of the threshold variable
the upper bound in the uniform prior of the threshold variable
T vector of evolution errors
the degree of differencing (one or two)