Helper function for Sampling parameters for ASV model
fit_paramsASV(data, sParams, evol_error, D)a list containing 4 sets of parameters
s_p_error_term: matrix containing mean and the variance from 10-componenet gaussian mixture (Omori et al. 2007)
s_mu: a vector containing the posterior sample of log variance h,
s_evolParams0: a list containing posterior samples of parameters associated with the variance of first D observation of the log variance term, h.
s_evolParams: a list containing posterior samples parameters associated with the variance of D to the last observations of the log variance temr , h.
the T x 1 vector of time series observations.
list from the previous run of fit_paramsASV function or init_paramsASV function
the evolution error distribution; must be one of 'DHS' (dynamic horseshoe prior), 'HS' (horseshoe prior), 'BL' (Bayesian lasso), or 'NIG' (normal-inverse-gamma prior)
degree of differencing (D = 1, or D = 2)