PointFore: Interpretation of Point Forecasts as State-Dependent Quantiles and Expectiles

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 <pschmidte at gmail.com>
License: CC0
NeedsCompilation: no
Language: en-US
Materials: README
CRAN checks: PointFore results


Reference manual: PointFore.pdf
Vignettes: GDP Greenbook
Tutorial for PointFore


Package source: PointFore_0.2.0.tar.gz
Windows binaries: r-devel: PointFore_0.2.0.zip, r-release: PointFore_0.2.0.zip, r-oldrel: PointFore_0.2.0.zip
macOS binaries: r-release (arm64): PointFore_0.2.0.tgz, r-oldrel (arm64): PointFore_0.2.0.tgz, r-release (x86_64): PointFore_0.2.0.tgz, r-oldrel (x86_64): PointFore_0.2.0.tgz


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