Package: PointFore 0.2.0.9000

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) <arxiv:1506.01917> for more details on the identification and estimation of a directive behind a point forecast.

Authors:Patrick Schmidt [aut, cre]

PointFore_0.2.0.9000.tar.gz
PointFore_0.2.0.9000.zip(r-4.7-any)PointFore_0.2.0.9000.zip(r-4.6-any)PointFore_0.2.0.9000.zip(r-4.5-any)
PointFore_0.2.0.9000.tgz(r-4.6-any)PointFore_0.2.0.9000.tgz(r-4.5-any)
PointFore_0.2.0.9000.tar.gz(r-4.7-any)PointFore_0.2.0.9000.tar.gz(r-4.6-any)
PointFore_0.2.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PointFore/json (API)

# Install 'PointFore' in R:
install.packages('PointFore', repos = c('https://schmidtpk.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/schmidtpk/pointfore/issues

Datasets:
  • GDP - Real GDP realized values and one quarter ahead Greenbook forecasts
  • precipitation - Daily accumulated precipitation

On CRAN:

Conda:

4.59 score 26 scripts 275 downloads 10 exports 72 dependencies

Last updated from:c10c5cba01. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR159
source / vignettesOK241
linux-release-x86_64ERROR178
macos-release-arm64ERROR153
macos-oldrel-arm64ERROR142
windows-develERROR109
windows-releaseERROR107
windows-oldrelERROR91
wasm-releaseOK129

Exports:constantestimate.functionalexpectileslaglogistic_linearprobit_breakprobit_linearprobit_spline2probit_spline3quantiles

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegmmgtableisobandlabelinglatticelifecyclelme4lmtestlubridatemagrittrMASSMatrixMatrixModelsmgcvminqamodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7sandwichscalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDateurcautf8vctrsviridisLitewithrzoo

GDP Greenbook forecasts
Data | Analysis | Replication of the results in "Interpretation of Point Forecasts with Unknown Directive" by Schmidt, Katzfuss and Gneiting | Different information sets (instrumental vectors) | Different specification models | Different state variables
Rendered fromGDP.Rmdusingknitr::rmarkdown

Last update: 2020-12-07
Started: 2019-01-23

Precipitation forecasts
Data | Analysis
Rendered fromPrecipitation.Rmdusingknitr::rmarkdown

Last update: 2020-12-07
Started: 2018-12-28

Tutorial for PointFore
Introduction | Simulated Example | Generate data | Estimation of the functional | Plot results | Wald tests | Creating your own specification models | Applying non-standard instruments
Rendered fromTutorial.Rmdusingknitr::rmarkdown

Last update: 2019-02-12
Started: 2018-06-21