summary method for vharlse class.
# S3 method for vharlse
summary(object, ...)# S3 method for summary.vharlse
print(x, digits = max(3L, getOption("digits") - 3L), signif_code = TRUE, ...)
# S3 method for summary.vharlse
knit_print(x, ...)
summary.vharlse
class additionally computes the following
namesVariable names
totobsTotal number of the observation
obsSample size used when training = totobs - p
p3
weekOrder for weekly term
monthOrder for monthly term
coefficientsCoefficient Matrix
callMatched call
processProcess: VAR
covmatCovariance matrix of the residuals
corrmatCorrelation matrix of the residuals
rootsRoots of characteristic polynomials
is_stableWhether the process is stable or not based on roots
log_liklog-likelihood
icInformation criteria vector
AIC - AIC
BIC - BIC
HQ - HQ
FPE - FPE
A vharlse object
not used
summary.vharlse object
digit option to print
Check significant rows (Default: TRUE)
Lütkepohl, H. (2007). New Introduction to Multiple Time Series Analysis. Springer Publishing.
Corsi, F. (2008). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics, 7(2), 174-196.
Baek, C. and Park, M. (2021). Sparse vector heterogeneous autoregressive modeling for realized volatility. J. Korean Stat. Soc. 50, 495-510.