Commit 45d7e384 authored by pbac's avatar pbac
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Submitted 1.0.0

parent 2b10bc1f
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^.*\.Rhistory$
^cran-comments.md
^README\.Rmd$
^.gitlab
^README.md
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Package: onlineforecast
Type: Package
Title: Forecast Modelling for Online Applications
Version: 0.10.1
Description: A framework for fitting adaptive forecasting models. Provides a way to use forecasts as input to models, e.g. weather forecasts for energy related forecasting. The models can be fitted recursively and can easily be setup for updating parameters when new data arrives. See the included vignettes, the website <https://onlineforecasting.org> and the paper "Short-term heat load forecasting for single family houses" <doi:10.1016/j.enbuild.2013.04.022>.
Version: 1.0.0
Description: A framework for fitting adaptive forecasting models. Provides a way to use forecasts as input to models, e.g. weather forecasts for energy related forecasting. The models can be fitted recursively and can easily be setup for updating parameters when new data arrives. See the included vignettes, the website <https://onlineforecasting.org> and the pre-print paper "onlineforecast: An R package for adaptive and recursive forecasting" <arXiv:2109.12915>.
License: GPL-3
Encoding: UTF-8
LazyData: true
......
<!---usethis::use_readme_rmd() -->
<!-- README.md is generated from README.Rmd. Please edit that file -->
# onlineforecast <img src='misc-R/figures/onlineforecast.png' align="right" height="139" />
<!--
usethis::use_cran_badge()
usethis::use_lifecycle_badge("stable")
usethis::use_logo("misc-R/figures/onlineforecast.png")
-->
<!-- badges: start -->
[![CRAN
status](https://www.r-pkg.org/badges/version/onlineforecast)](https://CRAN.R-project.org/package=onlineforecast)
[![Lifecycle:
stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://www.tidyverse.org/lifecycle/#stable)
[![CRAN RStudio mirror
downloads](http://cranlogs.r-pkg.org/badges/onlineforecast)](https://cran.r-project.org/package=onlineforecast)
<!-- badges: end -->
The *onlineforecast* R package computes new forecasts whenever new
observations becomes available by using recursive estimation. The
package makes it easy to setup models to be used for online forecasting,
where the user can create their own online forecast-set-up with their
own inputs. The pacakge is created based on the authors long experience
of formulating time series models which use weather forecasts as inputs.
The challenge comes from the overlapping time series as the forecast
needs to be updated whenever the weather forecast is updated.
See more on [onlineforecast](https://onlineforecasting.org/) webpage
## Installation
You can install the released version of onlineforecast from
[CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("onlineforecast")
```
## Example
See examples on how to use the package on the website,
[onlineforecast](https://onlineforecasting.org/examples.html) where
multiple vignettes demonstrate how it works.
#----------------------------------------------------------------
# v1.0.0
We have not changed much, but we have written a paper and submitted it to
JSS. So now we have set the major version forward.
#----------------------------------------------------------------
# v0.10.0
......@@ -9,7 +17,6 @@ should be fully backward compatible.
#----------------------------------------------------------------
# v0.9.3
# Response to review of v0.9.2 by Uwe Ligges
......
citHeader("To cite onlineforecast in publications use:")
citEntry(
entry = "Article",
title = "Short-term heat load forecasting for single family houses",
author = "Peder Bacher and Henrik Madsen and Henrik Aalborg Nielsen and Bengt Perers",
journal = "Energy and Buildings",
year = "2013",
volume = "65",
number = "0",
pages = "101-112",
doi = "10.1016/j.enbuild.2013.04.022",
url = "https://onlineforecasting.org",
textVersion = paste(
"We are in process of writing a journal paper about the package, but for now we referer to the paper 'Short-term heat load forecasting for single family houses', in which the implemented modelling is described."
)
title = "onlineforecast: An R package for adaptive and recursive forecasting",
author = "Peder Bacher and Hjörleifur G. Bergsteinsson and Linde Frölke and Mikkel L. Sørensen and Julian Lemos-Vinasco and Jon Liisberg and Jan Kloppenborg Møller and Henrik Aalborg Nielsen and Henrik Madsen",
Journal = "test",
year = "2021",
eprint = "2109.12915",
archivePrefix="arXiv",
primaryClass="stat.CO",
url = "https://arxiv.org/abs/2109.12915",
textVersion = "The article \"onlineforecast: An R package for adaptive and recursive forecasting\", see https://arxiv.org/abs/2109.12915. This is the pre-print version submitted to Journal of Statistical Software."
)
citEntry(
entry = "Manual",
title = "{{onlineforecast}: Forecast Modelling for Online Applications}",
author = "Peder Bacher and Hjörleifur G. Bergsteinsson",
year = "2021",
note = "R package version 0.10.1",
url = "https://onlineforecasting.org"
note = "R package version 1.0.0",
url = "https://onlineforecasting.org",
textVersion = ""
)
......@@ -56,21 +56,21 @@ library(roxygen2)
# # Run tests in a single file
# test_file("tests/testthat/test-rls-heat-load.R")
# ----------------------------------------------------------------
# Build the package
document()
build(".", vignettes=TRUE)
# The version (change only in DESCRIPTION)
# The version (move the value from DESCRIPTION to other places, so only update it in DESCRIPTION)
txt <- scan("DESCRIPTION", character())
ver <- txt[which(txt == "Version:") + 1]
(ver <- txt[which(txt == "Version:") + 1])
# Update CITATION (change the year manually)
txt2 <- scan("inst/CITATION", character(), sep="#", quote="")
txt2[grep("R package version",txt2)] <- paste0(' note = "R package version ',ver,'",')
write.table(txt2, "inst/CITATION", row.names=FALSE, col.names=FALSE, quote=FALSE)
# ----------------------------------------------------------------
# Build the package
document()
build(".", vignettes=TRUE)
# Install it
gzfile <- paste0("../onlineforecast_",ver,".tar.gz")
install.packages(gzfile)
......
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