{"id":26895880,"url":"https://github.com/mittelmark/snha","last_synced_at":"2026-03-06T23:31:01.481Z","repository":{"id":141948932,"uuid":"600871773","full_name":"mittelmark/snha","owner":"mittelmark","description":"St. Nicolas House Algorithm implementation in R - predicting correlation networks using association chains","archived":false,"fork":false,"pushed_at":"2025-12-11T12:18:09.000Z","size":180,"stargazers_count":6,"open_issues_count":1,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-12-12T11:52:31.832Z","etag":null,"topics":["correlation-analysis","network","network-analysis","network-reconstruction","r-package"],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mittelmark.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2023-02-12T20:53:43.000Z","updated_at":"2025-12-11T12:18:13.000Z","dependencies_parsed_at":"2024-07-06T21:26:36.468Z","dependency_job_id":"0872a67d-4093-4366-81df-df7b281a7ad0","html_url":"https://github.com/mittelmark/snha","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":"mittelmark/Rpkg","purl":"pkg:github/mittelmark/snha","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mittelmark%2Fsnha","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mittelmark%2Fsnha/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mittelmark%2Fsnha/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mittelmark%2Fsnha/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mittelmark","download_url":"https://codeload.github.com/mittelmark/snha/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mittelmark%2Fsnha/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30203322,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-06T19:07:06.838Z","status":"ssl_error","status_checked_at":"2026-03-06T18:57:34.882Z","response_time":250,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["correlation-analysis","network","network-analysis","network-reconstruction","r-package"],"created_at":"2025-04-01T02:58:57.133Z","updated_at":"2026-03-06T23:31:01.459Z","avatar_url":"https://github.com/mittelmark.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![license](https://img.shields.io/badge/License%20(MIT)-lightgray.svg)](https://opensource.org/license/bsd)\n[![Release](https://img.shields.io/github/v/release/mittelmark/snha.svg?label=current+release)](https://github.com/mittelmark/snha/releases)\n![Downloads](https://img.shields.io/github/downloads/mittelmark/snha/total)\n![Commits](https://img.shields.io/github/commits-since/mittelmark/snha/latest)\n[![Manual\u0026nbsp;PDF](https://img.shields.io/badge/Manual%20(PDF)-blue)](https://github.com/mittelmark/snha/releases/latest/download/snha-manual.pdf)\n[![Vignette\u0026nbsp;PDF](https://img.shields.io/badge/Vignette%20(PDF)-blue)](https://github.com/mittelmark/snha/releases/latest/download/snha-tutorial.pdf)\n[![Vignette\u0026nbsp;HTML](https://img.shields.io/badge/Vignette%20(HTML)-blue)](https://github.com/mittelmark/snha/releases/latest/download/tutorial.html)\n\n# Snha package\n\nR package which implements the St. Nicolas House Algorithm (SNHA) for\nconstructing networks of correlated variables using a ranking of the pairwise\ncorrelation values. The package contains the R code for the papers:\n\n- Groth, D., Scheffler, C., \u0026 Hermanussen, M. (2019). Body height in stunted\n  Indonesian children depends directly on parental education and not via\n  a nutrition mediated pathway-Evidence from tracing association chains by St.\n  Nicolas House Analysis. Anthropologischer Anzeiger, 76(5), 445-451. \n  [https://doi.org/10.1127/anthranz/2019/1027](https://doi.org/10.1127/anthranz/2019/1027)\n- Hermanussen, M., Aßmann, C., \u0026 Groth, D. (2021). Chain Reversion for Detecting \n  Associations in Interacting Variables—St. Nicolas House Analysis. \n  International journal of environmental research and public health, 18(4), 1741\n  [https://doi.org/10.3390/ijerph18041741](https://doi.org/10.3390/ijerph18041741)\n\nFor an implementation of the algorithm in Python look here\n[https://github.com/thake93/snha4py](https://github.com/thake93/snha4py).\n\n## CRAN Statistics\n\n* Downloads - total: ![](https://cranlogs.r-pkg.org/badges/grand-total/snha)\n* Downloads - monthly: ![](https://cranlogs.r-pkg.org/badges/snha)\n* Downloads - weekly: ![](https://cranlogs.r-pkg.org/badges/last-week/snha)\n\n## Installation\n\nEither install the package directly from CRAN as usually:\n\n```\ninstall.packages('snha')\n```\n\nFor installing the latest stable version directly from Github you can execute the following command in your R console:\n\n```\ninstall.packages(\n  \"https://github.com/mittelmark/snha/releases/download/v0.2.1/snha_0.2.1.tar.gz\",\n  repos=NULL);\n``` \n\nThereafter you can load the package and the vignette of the package like this:\n\n```\nlibrary(snha)\nvignette(\"tutorial\",package=\"snha)\ncitation(\"snha\")\n```\n\nOr to use the latest development version from the Github repository install it like this:\n\n```\nlibrary(remotes)\nremotes::install_github(\"https://github.com/mittelmark/snha\")\n```\n\n## Example\n\nThe package has a function `snha` where you give your data as input. The\nfunction creates an object of class `snha` which you can plot and\nexplore easily. Here an example just using the `swiss` data which are part of\nevery R installation:\n\n```r\n\u003e library(snha)\n\u003e library(MASS)\n\u003e data(swiss)\n\u003e colnames(swiss)=abbreviate(swiss)\n\u003e as=snha(swiss,method=\"spearman\")\n\u003e plot(as)\n\u003e plot(as,layout=\"sam\",vertex.size=8)\n\u003e ls(as)\n[1] \"alpha\"         \"chains\"        \"data\"          \"method\"\n[5] \"p.values\"      \"probabilities\" \"sigma\"         \"theta\"\n[9] \"threshold\"\n\u003e as$theta\n     Frtl Agrc Exmn Edct Cthl In.M\nFrtl    0    0    1    0    0    1\nAgrc    0    0    0    1    0    0\nExmn    1    0    0    1    1    0\nEdct    0    1    1    0    0    0\nCthl    0    0    1    0    0    0\nIn.M    1    0    0    0    0    0\n\n```\n\n![](https://raw.githubusercontent.com/mittelmark/snha/main/img/swiss-spearman.png)\n\nThe theta object contains the adjacency matrix with the edges for the found\ngraph. For more details consult the package vignette:\n`vignette(package=\"snha\",\"tutorial\")` or the manual package of the package\n`?snha` or `?'snha-package'`.\n\n## Author and Copyright\n\nAuthor: Detlef Groth, University of Potsdam, Germany\n\nLicense: MIT License see the file [LICENSE](LICENSE) for details.\n\n## Contributors\n\nThe following persons have contributed to the package with ideas, testing, etc.:\n\n* Michael Hermanussen (Aschauhof, the algorithm idea)\n* Masiar Novine (University of Potsdam, evaluating different data generation methods and comparing the algorithm swit other approaches)\n* Tim Hake (University of Potsdam, Python port and critical discussions about directed edges)\n* Bernhard Bodenberger (University of Potsdam, evaluating the bootstrap performances and different parts of the algorithm)\n* Cedric Moris (University of Potsdam, evaluating different extensions of the basic algorithm)\n\n## Bug reporting\n\nIn case of bugs and suggestions, use the [issues](https://github.com/mittelmark/snha/issues) link on top.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmittelmark%2Fsnha","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmittelmark%2Fsnha","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmittelmark%2Fsnha/lists"}