coef.tegarch: Extraction methods for 'tegarch' objects

In betategarch: Simulation, Estimation and Forecasting of Beta-Skew-t-EGARCH Models

Extraction methods for 'tegarch' objects

Description

Extraction methods for objects of class 'tegarch' (i.e. the result of estimating a Beta-Skew-t-EGARCH model)

Usage

## S3 method for class 'tegarch'
coef(object, ...)
## S3 method for class 'tegarch'
fitted(object, verbose = FALSE, ...)
## S3 method for class 'tegarch'
logLik(object, ...)
## S3 method for class 'tegarch'
print(x, ...)
## S3 method for class 'tegarch'
residuals(object, standardised = TRUE, ...)
## S3 method for class 'tegarch'
summary(object, verbose = FALSE, ...)
## S3 method for class 'tegarch'
vcov(object, ...)

Arguments

object	an object of class 'tegarch'
x	an object of class 'tegarch'
verbose	logical. If FALSE (default) then only basic information is returned
standardised	logical. If TRUE (default) then the standardised residuals are returned. If FALSE then the scaled (by sigma) residuals are returned
...	additional arguments

Details

Empty

Value

coef:	A numeric vector containing the parameter estimates
fitted:	A zoo object. If verbose=FALSE (default), then the zoo object is a vector containing the fitted conditional standard deviations. If verbose = TRUE, then the zoo object is a matrix containing the return series y, fitted scale (sigma), fitted conditional standard deviation (stdev), fitted log-scale (lambda), dynamic component(s) (lambdadagger in the 1-component specification, lambda1dagger and lambda2dagger in the 2-compoment specification), the score (u), scaled residuals (epsilon) and standardised residuals (residstd)
logLik:	The value of the log-likelihood at the maximum
print:	Prints the most important parts of the estimation results
residuals:	A zoo object. If standardised = TRUE (default), then the zoo object is a vector with the standardised residuals. If standardised = FALSE, then the zoo vector contains the scaled residuals
summary:	A list. If verbose = FALSE, then only the most important entries are returned. If verbose = TRUE, then all entries apart from the 1st. (the y series) is returned
vcov:	The variance-covariance matrix of the estimated coefficents. The matrix is obtained by inverting the numerically estimated Hessian

Author(s)

Genaro Sucarrat, https://www.sucarrat.net/

References

C. Fernandez and M. Steel (1998), 'On Bayesian Modeling of Fat Tails and Skewness', Journal of the American Statistical Association 93, pp. 359-371, \Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.1080/01621459.1998.10474117")}

A. Harvey and G. Sucarrat (2014), 'EGARCH models with fat tails, skewness and leverage'. Computational Statistics and Data Analysis 76, pp. 320-338, \Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.1016/j.csda.2013.09.022")}

G. Sucarrat (2013), 'betategarch: Simulation, Estimation and Forecasting of First-Order Beta-Skew-t-EGARCH models'. The R Journal (Volume 5/2), pp. 137-147, ,\Sexpr[results=rd]{tools:::Rd_expr_doi("https://doi.org/10.32614/RJ-2013-034")}

See Also

tegarch, coef, fitted, logLik, predict.tegarch, print, residuals, summary, vcov

Examples

##simulate 1000 observations from model with default parameter values:
set.seed(123)
y <- tegarchSim(1000)

##estimate and store as 'mymodel':
mymod <- tegarch(y)

##print estimation result:
print(mymod)

##extract coefficients:
coef(mymod)

##extract log-likelihood:
logLik(mymod)

##plot fitted conditional standard deviations:
plot(fitted(mymod))

##plot all the fitted series:
plot(fitted(mymod, verbose=TRUE))

##histogram of standardised residuals:
hist(residuals(mymod))

betategarch documentation built on April 3, 2025, 9:54 p.m.