mtarNAIC {BMTAR} | R Documentation |
Compute NAIC of a MTAR model
Description
Compute the Non-linear Akaike information criterion (NAIC) of a “regime_model
” class object.
Usage
mtarNAIC(regimemodel)
Arguments
regimemodel |
object of class “ |
Details
Estimation of thresholds was made before starting the Bayesian procedure via the Non-linear Akaike information criterion (NAIC) (Tong, 1990), in MTAR model. The NAIC for a MTAR model with l regimes is:
Nj: number of observations in each regime.
Value
Return a list type object:
AICj |
numeric type, AIC for each regime |
NAIC |
numeric type, NAIC value |
Author(s)
Valeria Bejarano vbejaranos@unal.edu.co, Sergio Calderon sacalderonv@unal.edu.co & Andrey Rincon adrincont@unal.edu.co
References
Calderon, S. and Nieto, F. (2017) Bayesian analysis of multivariate threshold autoregress models with missing data. Communications in Statistics - Theory and Methods 46 (1):296–318. doi:10.1080/03610926.2014.990758.
Examples
data("datasim")
data = datasim
# Estimate number of regimes with NAIC
initial1 = mtarinipars(tsregime_obj = data$Sim,
list_model = list(pars = list(l = 2,
orders = list(pj = c(1,1),dj = c(1,1)), r = 0.2)))
estruc1 = mtarns(ini_obj = initial1,niter = 100,chain = TRUE,burn = 100)
initial2 = mtarinipars(tsregime_obj = data$Sim,
list_model = list(pars = list(l = 2,
orders = list(pj = c(1,1),dj = c(1,1)), r = 0.3)))
estruc2 = mtarns(ini_obj = initial2,niter = 100,chain = TRUE,burn = 100)
#NAIC
mtarNAIC(estruc1)
mtarNAIC(estruc2)