coef.tvgarchTest {tvgarch} | R Documentation |
Extraction functions for univarate 'tvgarchTest' objects
Description
Extraction functions for objects of class 'tvgarchTest'. Results from the estimation of the model under the null hypothesis, i.e., a GARCH(1,1) model, can be extracted similar to an object of class 'tvgarch' with the exception of functions print.tvgarchTest() and summary.tvgarchTest().
Usage
## S3 method for class 'tvgarchTest'
coef(object, ...)
## S3 method for class 'tvgarchTest'
fitted(object,
as.zoo = TRUE, ...)
## S3 method for class 'tvgarchTest'
logLik(object, ...)
## S3 method for class 'tvgarchTest'
nobs(object, ...)
## S3 method for class 'tvgarchTest'
plot(x, ...)
## S3 method for class 'tvgarchTest'
predict(object, n.ahead = 10, newxreg = NULL,
newindex = NULL, n.sim = 5000,
as.zoo = TRUE, verbose = FALSE, ...)
## S3 method for class 'tvgarchTest'
print(x, ...)
## S3 method for class 'tvgarchTest'
quantile(x, probs = 0.025, names = TRUE, type = 7,
as.zoo = TRUE, ...)
## S3 method for class 'tvgarchTest'
residuals(object, as.zoo = TRUE, ...)
## S3 method for class 'tvgarchTest'
summary(object, ...)
## S3 method for class 'tvgarchTest'
toLatex(object, digits = 4, ...)
## S3 method for class 'tvgarchTest'
vcov(object, ...)
Arguments
object |
an object of class 'tvgarchTest'. |
x |
an object of class 'tvgarchTest'. |
as.zoo |
logical. If |
n.ahead |
integer that determines how many steps ahead predictions should be generated. |
newxreg |
vector or matrix with the out-of-sample regressor values. |
newindex |
a |
n.sim |
integer, the number of simulations. |
verbose |
logical. If |
probs |
vector of probabilities. |
names |
logical, whether to return names or not. |
type |
integer that determines the algorithm used to compute the
quantile, see |
digits |
integer, the number of digits in the printed LaTeX code. |
... |
additional arguments. |
Value
coef: |
parameter estimates. |
fitted: |
fitted conditional variance. |
logLik: |
optimised log-likelihood (normal density) value. |
nobs: |
the number of observations used in the estimation. |
plot: |
plot of the fitted conditional volatility. |
predict: |
variance predictions. |
quantile: |
fitted quantiles, i.e. the conditional standard deviation times the empirical quantile of the standardised innovations. |
residuals: |
volatility standardised residuals. |
summary: |
summary of test result. |
vcov: |
coefficient variance-covariance matrix. |
Author(s)
Susana Campos-Martins
References
Cristina Amado and Timo Terasvirta (2013) Modelling volatility by variance decomposition, Journal of Econometrics 175, 142-153.
Cristina Amado and Timo Terasvirta (2014) Modelling changes in the unconditional variance of long stock return series, Journal of Empirical Finance 25, 15-35.
Susana Campos-Martins and Genaro Sucarrat (2024) Modeling Nonstationary Financial Volatility with the R Package tvgarch, Journal of Statistical Software 108, 1-38.
See Also
tvgarchTest
,
tvgarchSim
,
tvgarch
,
zoo
Examples
set.seed(123)
## Simulate from a TV(1)-GARCH(1,1) model (default):
ySim <- tvgarchSim(n = 1500)
## Test a GARCH(1,1) model against a TV(1)-GARCH(1,1) model:
yTest <- tvgarchTest(y = ySim)
## Print test and estimation results:
print(yTest)
## Estimated number of locations
summary(yTest)
## Extract and plot estimation results for GARCH(1,1) used in the test:
sigma2Test <- fitted(yTest)
plot(yTest)
## Estimate a TV(s)-GARCH(1,1) model:
s <- summary(yTest)
yEst <- tvgarch(y = ySim, order.g = s)