fit_paramsASV_n: Helper function for Sampling parameters for ASV model with a...

In dsp: Dynamic Shrinkage Process and Change Point Detection

Helper function for Sampling parameters for ASV model with a nugget Effect

Description

Helper function for Sampling parameters for ASV model with a nugget Effect

Usage

fit_paramsASV_n(data, sParams, evol_error, D)

Arguments

data	the T x 1 vector of time series observations.
sParams	list from the previous run of fit_paramsASV function or init_paramsASV function
evol_error	the evolution error distribution; must be one of 'DHS' (dynamic horseshoe prior), 'HS' (horseshoe prior), 'BL' (Bayesian lasso), or 'NIG' (normal-inverse-gamma prior)
D	degree of differencing (D = 1, or D = 2)

Value

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.

dsp documentation built on Aug. 21, 2025, 5:29 p.m.