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gets (version 0.40)

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

Description

Automated General-to-Specific (GETS) modelling of the mean and variance of a regression, and indicator saturation methods for detecting and testing for structural breaks in the mean, see Pretis, Reade and Sucarrat (2018) for an overview of the package. In advanced use, the estimator and diagnostics tests can be fully user-specified, see Sucarrat (2021) .

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Version

Install

install.packages('gets')

Monthly Downloads

648

Version

0.40

License

GPL (>= 2)

Homepage

https://CRAN.R-project.org/package=gets

Maintainer

Genaro Sucarrat

Last Published

July 28th, 2026

Functions in gets (0.40)

create.ISmatrices

Internal function to construct Indicator Saturation Matrices

Extraction functions for 'arx' objects

Methods and extraction functions for 'larch' objects

distorttestboot

Bootstrapped Jiao-Pretis-Schwarz Outlier Distortion Test

Extraction functions for 'gets' objects

Extraction functions for 'logitx' objects

Extraction functions for 'isat' objects

Diagnostics tests

Jiao-Pretis-Schwarz Outlier Distortion Test

General-to-Specific (GETS) Modelling of a heterogeneous log-ARCH-X model

General-to-Specific (GETS) modelling function

Equally Weighted Moving Average (EqWMA) of the pth. exponentiated values

General-to-Specific (GETS) Modelling 'lm' objects

General-to-Specific (GETS) Modelling

General-to-Specific (GETS) Modelling of objects of class 'logitx'

General-to-Specific (GETS) Modelling of an AR-X model (the mean specification) with log-ARCH-X errors (the log-variance specification).

Exporting results to EViews and STATA

General-to-Specific (GETS) Modelling 'isat' objects

General-to-Specific (GETS) and Indicator Saturation (ISAT) Modelling

Extracting Indicator Saturation Breakdates

Hoover and Perez (1999) data

Indicator Saturation Test

Generalised Method of Moment (GMM) estimation of linear models

Indicator Saturation

Computes the Average Value of an Information Criterion

Quarterly Norwegian year-on-year CPI inflation

Variance of the coefficient path

Make Indicator Matrices (Impulses, Steps, Trends)

Repeated Impulse Indicator Saturation

Simulate from a Multivariate Normal Distribution

Simulate from a dynamic logit-x model

Estimate an autoregressive logit model with covariates

Estimation of a logit model

Estimation of a log-variance model

periodicdummies

Make matrix of periodicity (e.g. seasonal) dummies

Create the regressors of the mean equation

IIS Consistency Correction

Extraction functions for 'arx', 'gets' and 'isat' objects

Consistency and Efficiency Correction for Impulse Indicator Saturation

regressorsVariance

Create regressors for a log-variance model

Recursive estimation

Generate LaTeX code of an estimation result

Jiao and Pretis Outlier Proportion and Count Tests

Daily Standard and Poor's 500 index data

Estimate a heterogeneous log-ARCH-X model

Variance forecasting with 'larch' models

IIS Efficiency Correction

outlierscaletest

Sum and Sup Scaling Outlier Tests

Forecasting with 'arx' models

Variance of the Impulse Indicator Saturation Gauge

Convert to 'isat' object

Internal function to carry out the block-wise GETS search

Internal function to loop Over Indicator Saturation Matrices with Block-Based GETS

ISadditionalblocksearch

Internal function to carry out additional Block Search in isat: Leave-One-Out Block Search for Excessive Indicators

Bias-correction of coefficients following general-to-specific model selection

Conditional Value-at-Risk (VaR) and Expected Shortfall (ES)

Estimate an AR-X model with log-ARCH-X errors

Convert to 'lm' object

Block-based General-to-Specific (GETS) modelling

Convert an object to class 'arx'