https://www.ecmwf.int/>) and GDP growth Greenbook data by the US Federal Reserve. See Schmidt, Katzfuss and Gneiting (2015) <doi:10.48550/arXiv.1506.01917> for more details on the identification and estimation of a directive behind a point forecast.">

PointFore: Interpretation of Point Forecasts as State-Dependent Quantiles and Expectiles (original) (raw)

Estimate specification models for the state-dependent level of an optimal quantile/expectile forecast. Wald Tests and the test of overidentifying restrictions are implemented. Plotting of the estimated specification model is possible. The package contains two data sets with forecasts and realizations: the daily accumulated precipitation at London, UK from the high-resolution model of the European Centre for Medium-Range Weather Forecasts (ECMWF, <https://www.ecmwf.int/>) and GDP growth Greenbook data by the US Federal Reserve. See Schmidt, Katzfuss and Gneiting (2015) <doi:10.48550/arXiv.1506.01917> for more details on the identification and estimation of a directive behind a point forecast.

Version: 0.2.0
Depends: R (≥ 3.2.0)
Imports: gmm, boot, car, ggplot2, MASS, stats, lubridate, sandwich
Suggests: knitr, rmarkdown, testthat, spelling
Published: 2019-02-22
DOI: 10.32614/CRAN.package.PointFore
Author: Patrick Schmidt [aut, cre]
Maintainer: Patrick Schmidt
License: CC0
NeedsCompilation: no
Language: en-US
Materials: README
CRAN checks: PointFore results

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