Package: hdflex 0.3.0

hdflex: High-Dimensional Aggregate Density Forecasts

Provides a forecasting method that efficiently maps vast numbers of (scalar-valued) signals into an aggregate density forecast in a time-varying and computationally fast manner. The method proceeds in two steps: First, it transforms a predictive signal into a density forecast and, second, it combines the resulting candidate density forecasts into an ultimate aggregate density forecast. For a detailed explanation of the method, please refer to Adaemmer et al. (2023) <doi:10.2139/ssrn.4342487>.

Authors:Sven Lehmann [aut, cre, cph], Philipp Adämmer [aut], Rainer Schüssler [aut]

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NEWS

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

Peer review:

Bug tracker:https://github.com/lehmasve/hdflex/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

ensemble-learningforecast-combinationforecastinghigh-dimensionalitytime-series

4.08 score 3 stars 1 scripts 201 downloads 3 exports 37 dependencies

Last updated 9 days agofrom:364da1d67c. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 14 2024
R-4.5-win-x86_64OKNov 14 2024
R-4.5-linux-x86_64OKNov 14 2024
R-4.4-win-x86_64OKNov 14 2024
R-4.4-mac-x86_64OKNov 14 2024
R-4.4-mac-aarch64OKNov 14 2024
R-4.3-win-x86_64OKNov 14 2024
R-4.3-mac-x86_64OKNov 14 2024
R-4.3-mac-aarch64OKNov 14 2024

Exports:dscstsctvc

Dependencies:backportscheckmateclicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigplyrR6RColorBrewerRcppRcppArmadilloRcppThreadreshape2rlangscalesstringistringrtibbleutf8vctrsviridisLitewithr