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name: Draft paper PDF
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on:
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push:
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paths:
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- paper/**
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- .github/workflows/draft-pdf.yml
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jobs:
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paper:
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runs-on: ubuntu-latest
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name: Paper Draft
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steps:
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- name: Checkout
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uses: actions/checkout@v4
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- name: Build draft PDF
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uses: openjournals/openjournals-draft-action@master
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with:
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journal: joss
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paper-path: paper/paper.md
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- name: Upload
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uses: actions/upload-artifact@v4
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with:
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name: paper
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path: paper/paper.pdf

paper/paper.bib

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@article{jordan_evaluating_2019,
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title={Evaluating Probabilistic Forecasts with scoringRules},
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volume={90},
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url={https://www.jstatsoft.org/index.php/jss/article/view/v090i12},
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doi={10.18637/jss.v090.i12},
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abstract={Probabilistic forecasts in the form of probability distributions over future events have become popular in several fields including meteorology, hydrology, economics, and demography. In typical applications, many alternative statistical models and data sources can be used to produce probabilistic forecasts. Hence, evaluating and selecting among competing methods is an important task. The scoringRules package for R provides functionality for comparative evaluation of probabilistic models based on proper scoring rules, covering a wide range of situations in applied work. This paper discusses implementation and usage details, presents case studies from meteorology and economics, and points to the relevant background literature.},
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number={12},
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journal={Journal of Statistical Software},
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author={Jordan, Alexander and Krüger, Fabian and Lerch, Sebastian},
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year={2019},
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pages={1-37}
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}

paper/paper.md

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---
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title: 'scoringrules: probabilistic forecast evaluation'
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tags:
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- python
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- scoring rules
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- probabilistic
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- forecasting
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authors:
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- name: Francesco Zanetta
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orcid: 0000-0003-4954-4298
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equal-contrib: true
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affiliation: 1
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- name: Sam Allen
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orcid: 0000-0003-1971-8277
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equal-contrib: true
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affiliation: 2
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affiliations:
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- name: Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
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index: 1
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- name: Institute of Statistics, Karlsruhe Institute of Technology, Karlsruhe, Germany
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index: 2
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date: 7 April 2025
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bibliography: paper.bib
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---
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# Summary (needed)
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A summary describing the high-level functionality and purpose of the software for a diverse, non-specialist audience.
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# Statement of need (needed)
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A Statement of need section that clearly illustrates the research purpose of the software and places it in the context of related work.
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# Mathematics
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Single dollars ($) are required for inline mathematics e.g. $f(x) = e^{\pi/x}$
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Double dollars make self-standing equations:
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$$\Theta(x) = \left\{\begin{array}{l}
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0\textrm{ if } x < 0\cr
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1\textrm{ else}
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\end{array}\right.$$
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You can also use plain \LaTeX for equations
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\begin{equation}\label{eq:fourier}
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\hat f(\omega) = \int_{-\infty}^{\infty} f(x) e^{i\omega x} dx
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\end{equation}
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and refer to \autoref{eq:fourier} from text.
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# Citations
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Citations to entries in paper.bib should be in
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[rMarkdown](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html)
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format.
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If you want to cite a software repository URL (e.g. something on GitHub without a preferred
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citation) then you can do it with the example BibTeX entry below for @fidgit.
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For a quick reference, the following citation commands can be used:
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- `@author:2001` -> "Author et al. (2001)"
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- `[@author:2001]` -> "(Author et al., 2001)"
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- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)"
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[@jordan_evaluating_2019]
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# Figures
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Figures can be included like this:
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<!-- ![Caption for example figure.\label{fig:example}](figure.png) -->
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<!-- and referenced from text using \autoref{fig:example}. -->
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<!-- Figure sizes can be customized by adding an optional second parameter: -->
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<!-- ![Caption for example figure.](figure.png){ width=20% } -->
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# Acknowledgements (needed)
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This is related to financial support.
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# References (needed)
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Will be automatically generated (?).

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