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profoc

Probabilistic Forecast Combination Using CRPS Learning

Installation

About

Combine probabilistic forecasts using CRPS learning algorithms proposed in Berrisch, Ziel (2021) doi:10.1016/j.jeconom.2021.11.008. The package implements multiple online learning algorithms like Bernstein online aggregation; see Wintenberger (2014) . Quantile regression is also implemented for comparison purposes. Model parameters can be tuned automatically with respect to the loss of the forecast combination. Methods like predict(), update(), plot() and print() are available for convenience. This package utilizes the optim C++ library for numeric optimization .

Citation profoc citation info
profoc.berrisch.biz
github.com/BerriJ/profoc
Bug report File report

Key Metrics

Version 1.3.2
R ≥ 4.3.0
Published 2024-03-25 30 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks profoc results
Language en-US

Downloads

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Last 30 days 517 +22%
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Last 365 days 5.088 -2%

Maintainer

Maintainer

Jonathan Berrisch

Jonathan@Berrisch.biz

Authors

Jonathan Berrisch

aut / cre

Florian Ziel

aut

Material

README
NEWS
Reference manual
Package source

In Views

TimeSeries

Vignettes

Using the C++ Interface
Production
Introduction

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

profoc archive

Depends

R ≥ 4.3.0

Imports

Rcpp ≥ 1.0.5
Matrix
abind
methods
lifecycle
generics
tibble
ggplot2

Suggests

testthat ≥ 3.0.0
gamlss.dist
knitr
rmarkdown
dplyr

LinkingTo

Rcpp
RcppArmadillo ≥ 0.10.7.5.0
RcppProgress
splines2 ≥ 0.4.4
rcpptimer ≥ 1.1.0