gets (version 0.2)

gets-package: General-to-Specific (GETS) Modelling and Indicator Saturation Methods

Description

Automated multi-path General-to-Specific (GETS) modelling of the mean and variance of a regression, and indicator saturation methods for detecting structural breaks in the mean. The mean can be specified as an autoregressive model with covariates (an 'AR-X' model), and the variance can be specified as a log-variance model with covariates (a 'log-ARCH-X' model). The four main functions of the package are arx, getsm, getsv and isat. The first function, arx, estimates an AR-X model with log-ARCH-X errors. The second function, getsm, undertakes GETS model selection of the mean specification of an arx object. The third function, getsv, undertakes GETS model selection of the log-variance specification of an arx object. The fourth function, isat, undertakes GETS model selection of an indicator saturated mean specification. The package also provides auxiliary functions used by the main functions, in addition to extraction functions (mainly S3 methods).

Details

ll{ Package: gets Type: Package Version: 2.0 Date: 2014-12-22 License: GPL-2 } Most of the code was originally developed in relation with G. Sucarrat and A. Escribano (2012): 'Automated Financial Model Selection: General-to-Specific Modelling of the Mean and Volatility Specifications', Oxford Bulletin of Economics and Statistics 74, Issue 5 (October), pp. 716-735. Subsequently, Felix Pretis and James Reade joined for the development of the isat code and related functions

References

G. Sucarrat and A. Escribano (2012): 'Automated Financial Model Selection: General-to-Specific Modelling of the Mean and Volatility Specifications', Oxford Bulletin of Economics and Statistics 74, Issue 5 (October), pp. 716-735 Carlos Santos, Hendry, David, F. and Johansen, Soren (2007): 'Automatic selection of indicators in a fully saturated regression'. Computational Statistics, vol 23:1, pp.317-335 Jurgen, A. Doornik, Hendry, David F., and Pretis, Felix (2013): 'Step Indicator Saturation', Oxford Economics Discussion Paper, 658.

See Also

arx, getsm, getsv, isat

Examples

##Simulate from an AR(1):
set.seed(123)
y <- arima.sim(list(ar=0.4), 100)

##Estimate an AR(2) with intercept as mean specification
##and a log-ARCH(4) as log-volatility specification:
myModel <- arx(y, mc=TRUE, ar=1:2, arch=1:4)

##GETS model selection of the mean of myModel:
simpleMean <- getsm(myModel)

##GETS model selection of the log-variance of myModel:
simpleVar <- getsv(myModel)

##results:
print(simpleMean)
print(simpleVar)

##impulse indicator saturation of an iid normal series:
set.seed(123)
y <- rnorm(30)
isat(y)