Data

Tools

Indexes

Applications

Experiments

Open Source Science

threshr

Threshold Selection and Uncertainty for Extreme Value Analysis

https://github.com/paulnorthrop/threshr

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 1 committers (100.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (17.0%) to scientific vocabulary

Keywords

extreme-value-statistics extremes generalized inference pareto plot prediction threshold threshold-selection uncertainty
Last synced: 6 months ago · JSON representation

Repository

Threshold Selection and Uncertainty for Extreme Value Analysis

Basic Info
Statistics
  • Stars: 7
  • Watchers: 1
  • Forks: 2
  • Open Issues: 0
  • Releases: 7
Topics
extreme-value-statistics extremes generalized inference pareto plot prediction threshold threshold-selection uncertainty
Created over 8 years ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog License

README.Rmd 

---
output: github_document
---



```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
```

# threshr

[![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/paulnorthrop/threshr?branch=master&svg=true)](https://ci.appveyor.com/project/paulnorthrop/threshr)
[![R-CMD-check](https://github.com/paulnorthrop/threshr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/paulnorthrop/threshr/actions/workflows/R-CMD-check.yaml)
[![Coverage Status](https://codecov.io/github/paulnorthrop/threshr/coverage.svg?branch=master)](https://app.codecov.io/github/paulnorthrop/threshr?branch=master)
[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/threshr)](https://cran.r-project.org/package=threshr)
[![Downloads (monthly)](https://cranlogs.r-pkg.org/badges/threshr?color=brightgreen)](https://cran.r-project.org/package=threshr)
[![Downloads (total)](https://cranlogs.r-pkg.org/badges/grand-total/threshr?color=brightgreen)](https://cran.r-project.org/package=threshr)

## Threshold Selection and Uncertainty for Extreme Value Analysis

### What does threshr do?

The `threshr` package deals primarily with the selection of thresholds for use in extreme value models. It also performs predictive inferences about future extreme values. These inferences can either be based on a single threshold or on a weighted average of inferences from multiple thresholds.  The weighting reflects an estimated measure of the predictive performance of the threshold and can incorporate prior probabilities supplied by a user.  At the moment only the simplest case, where the data can be treated as independent identically distributed observations, is considered, as described in [Northrop et al. (2017)](https://doi.org/10.1111/rssc.12159).  Future releases will tackle more general situations.  

### A simple example

The main function in the threshr package is `ithresh`.  It uses Bayesian leave-one-out cross-validation to compare the extreme value predictive ability resulting from the use of each of a user-supplied set of thresholds.  The following code produces a threshold diagnostic plot using a dataset `gom` containing 315 storm peak significant waveheights.  We set a vector `u_vec` of thresholds; call `ithresh`, supplying the data and thresholds; and use then plot the results. In this minimal example (`ithresh` has further arguments) thresholds are judged in terms of the quality of prediction of whether the validation observation lies above the highest threshold in `u_vec` and, if it does, how much it exceeds this highest threshold.

```{r, eval = FALSE}
library(threshr)
u_vec_gom <- quantile(gom, probs = seq(0, 0.9, by = 0.05))
gom_cv <- ithresh(data = gom, u_vec = u_vec_gom)
plot(gom_cv)
```

### Installation

To get the current released version from CRAN:

```{r installation, eval = FALSE}
install.packages("threshr")
```

### Vignette

See `vignette("threshr-vignette", package = "threshr")` for an overview of the package.

Owner

  • Name: Paul Northrop
  • Login: paulnorthrop
  • Kind: user

GitHub Events

Total
  • Issues event: 2
  • Watch event: 1
  • Issue comment event: 1
  • Push event: 2
Last Year
  • Issues event: 2
  • Watch event: 1
  • Issue comment event: 1
  • Push event: 2

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 421
  • Total Committers: 1
  • Avg Commits per committer: 421.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 16
  • Committers: 1
  • Avg Commits per committer: 16.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Paul Northrop p****p@u****k 421
Committer Domains (Top 20 + Academic)
ucl.ac.uk: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 2
  • Total pull requests: 1
  • Average time to close issues: over 4 years
  • Average time to close pull requests: about 8 hours
  • Total issue authors: 2
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 2.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • hadley (1)
  • yeliuhrw (1)
Pull Request Authors
  • katrinleinweber (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 298 last-month
  • Total docker downloads: 43,390
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 7
  • Total maintainers: 1
cran.r-project.org: threshr

Threshold Selection and Uncertainty for Extreme Value Analysis

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 298 Last month
  • Docker Downloads: 43,390
Rankings
Forks count: 17.8%
Stargazers count: 22.5%
Dependent packages count: 29.8%
Average: 31.8%
Dependent repos count: 35.5%
Downloads: 53.6%
Maintainers (1)
p.northrop@ucl.ac.uk
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.3.0 depends
  • graphics * imports
  • methods * imports
  • revdbayes >= 1.3.4 imports
  • rust >= 1.2.2 imports
  • stats * imports
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests