General-to-Specific (GETS) Model Selection

Documentation for package ‘AutoSEARCH’ version 1.2

AutoSEARCH-package	General-to-Specific (GETS) Model selection
AutoSEARCH	General-to-Specific (GETS) Model selection
eqwma	Equally Weighted Moving Average (EqWMA) of the pth. exponentiated values
gedestp	Estimates the shape parameter of a standardised Generalised Error Distribution (GED)
gedlogl	Log-likelihood of a standardised Generalised Error Distribution (GED)
gets.mean	General-to-Specific (GETS) model selection of the mean specification
gets.vol	General-to-Specific (GETS) model selection of a log-volatility specification
gLag	Lag a series
gLog.ep	Adjust for zero values and compute log(abs(e)^p)
info.criterion	Computes the the value of an information criterion
jb.test	Jarque-Bera test for normality
leqwma	The logarithm of an Equally Weighted Moving Average (EqWMA) of the pth. exponentiated absolute values
ols.fit1	Fast and accurate OLS estimation by means of QR decomposition
ols.fit2	Fast and accurate OLS estimation by means of QR decomposition
regs.mean.sm	Creates the regressors of the mean specification of a SEARCH model
regs.vol.sm	Creates the regressors of the log-volatility specification
skewness.test	Chi-square test skewness in the standardised residuals
sm	Estimates a SEARCH model, that is, a model with an AR-X mean specification and a log-ARCH-X log-volatility specification