Description Details Author(s) References See Also Examples

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 (optionally) 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).

Package: | gets |

Type: | Package |

Version: | 0.12 |

Date: | 2017-02-18 |

License: | GPL-2 |

The code originated 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

Felix Pretis, http://www.felixpretis.org/

James Reade, https://sites.google.com/site/jjamesreade/

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

Maintainer: Genaro Sucarrat

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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ```
##Simulate from an AR(1):
set.seed(123)
y <- arima.sim(list(ar=0.4), 60)
##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 modelling of the mean of myModel:
simpleMean <- getsm(myModel)
##GETS modelling of the log-variance of myModel:
simpleVar <- getsv(myModel)
##results:
print(simpleMean)
print(simpleVar)
##step indicator saturation of an iid normal series:
set.seed(123)
y <- rnorm(30)
isat(y)
``` |

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