🕷️ Crawler Inspector

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Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 79 (from laksa190)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa079.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://tquant.eu/online-learning-contents/shiny-r-apps/james-stein-estimator/\')), getAhrefsUnparsedNoserviceFromURL(\'https://tquant.eu/online-learning-contents/shiny-r-apps/james-stein-estimator/\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/tquant.eu\/online-learning-contents\/shiny-r-apps\/james-stein-estimator\/","crawl_time":1776200415,"first_indexed_time":1508912733,"http_code":200,"src_unparsed":"eu,tquant!\/online-learning-contents\/shiny-r-apps\/james-stein-estimator\/ s443","src_root_hash":"6820862561481679679","history_drop_reason":null,"meta_title":"James-Stein estimator – Tools for Teaching Quantitative Thinking","meta_descriptions":[],"attrs_boilerpipe_text":"Skip to content\nTquanT\nAbout TquanT\nTquanT Consortium\nMobilities\n2016 – Lisbon\n2017 – Graz\nProgramme\nTravel Information\n2018 – Glasgow\nProgramme\nPreparation for the Seminar\nTravel Information\n2019 – Balatonföldvär\nProgramme\nStudent Project Proposals\nOnline Learning Contents\nMoodle Server\nR Shiny Apps\nBayesian Statistics & Computation\nKnowledge Space Theory\nMultisensory Input\nProbability Theory\nModel Comparison\nMiscellaneous Apps\n2016 Seminar\n2017 Seminar\n2018 Seminar\n2019 Seminar\nNews\nContact\nHome\nOnline Learning Contents\nShiny R Apps\nJames-Stein estimator\nThe goal of this shiny app is to visualize the effect of shrinkage estimators and compare their performance to other estimators.\nSuccessor project QHELP approved\n10th July 2019\nTquanT Project Finished\n1st September 2018\nUpdated Privacy Statement\n26th May 2018\nGlasgow Apps Online\n19th April 2018\nAssumptions\nBayes\nClassical Test Theory\nConsortium App\nGeneralizability\nIntraclass Correlation\nItem Response Theory\nKnowledge Space Theory\nlearnr Tutorial\nMachine Learning\nMaximum Likelihood\nMixed Models\nModel Comparison\nMonte Carlo\nMultisensory Input\nNetwork Models\nParameter Estimation\nPower\nProbability Theory\nReproducibility\nSignal Detection Theory\nStatistical Learning\nStatistics\nStudent App\nStudent Presentation\nUtilities\nThis website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish.\nCookie settings\nACCEPT","attrs_markdown":"[Skip to content](https:\/\/tquant.eu\/online-learning-contents\/shiny-r-apps\/james-stein-estimator\/#content)\n\n[![TqzanT Logo - Tools for Teaching Quantitative Thinking](https:\/\/tquant.eu\/wp-content\/uploads\/2016\/08\/tquant.png)](https:\/\/tquant.eu\/)\n\n- [TquanT](https:\/\/tquant.eu\/)\n  - [About TquanT](https:\/\/tquant.eu\/tquant\/about-tquant\/)\n  - [TquanT Consortium](https:\/\/tquant.eu\/tquant\/tquant-consortium\/)\n- [Mobilities](https:\/\/tquant.eu\/mobilities\/)\n  - [2016 – Lisbon](https:\/\/tquant.eu\/mobilities\/2016-lisbon\/)\n  - [2017 – Graz](https:\/\/tquant.eu\/mobilities\/2017-graz\/)\n    - [Programme](https:\/\/tquant.eu\/mobilities\/2017-graz\/programme\/)\n    - [Travel Information](https:\/\/tquant.eu\/mobilities\/2017-graz\/travel-information\/)\n  - [2018 – Glasgow](https:\/\/tquant.eu\/mobilities\/2018-glasgow\/)\n    - [Programme](https:\/\/tquant.eu\/mobilities\/2018-glasgow\/programme\/)\n    - [Preparation for the Seminar](https:\/\/tquant.eu\/mobilities\/2018-glasgow\/preparation\/)\n    - [Travel Information](https:\/\/tquant.eu\/mobilities\/2018-glasgow\/travel-information\/)\n  - [2019 – Balatonföldvär](https:\/\/tquant.eu\/mobilities\/2019-balatonfoldvar\/)\n    - [Programme](https:\/\/tquant.eu\/mobilities\/2019-balatonfoldvar\/programme\/)\n    - [Student Project Proposals](https:\/\/tquant.eu\/mobilities\/2019-balatonfoldvar\/student-project-proposals\/)\n- [Online Learning Contents](https:\/\/tquant.eu\/online-learning-contents\/)\n  - [Moodle Server](https:\/\/tquant.eu\/online-learning-contents\/moodle-server\/)\n  - [R Shiny Apps](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/)\n    - [Bayesian Statistics & Computation](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/bayesian-statistics-computation\/)\n    - [Knowledge Space Theory](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/knowledge-space-theory\/)\n    - [Multisensory Input](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/multisensory-input\/)\n    - [Probability Theory](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/probability-theory\/)\n    - [Model Comparison](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/model-comparison\/)\n    - [Miscellaneous Apps](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/miscellaneous-apps\/)\n    - [2016 Seminar](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/2016-seminar\/)\n    - [2017 Seminar](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/2017-seminar\/)\n    - [2018 Seminar](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/2018-seminar\/)\n    - [2019 Seminar](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/2019-seminar\/)\n- [News](https:\/\/tquant.eu\/news\/)\n- [Contact](https:\/\/tquant.eu\/contact\/)\n\n# James-Stein estimator\n- [Home](https:\/\/tquant.eu\/)\n- [Online Learning Contents](https:\/\/tquant.eu\/online-learning-contents\/)\n- [Shiny R Apps](https:\/\/tquant.eu\/online-learning-contents\/shiny-r-apps\/)\n- James-Stein estimator\n\n[![](https:\/\/tquant.eu\/wp-content\/uploads\/2017\/05\/James-Stein.png)](https:\/\/r.tquant.eu\/UvA\/JamesSteinEstimator\/)  \n The goal of this shiny app is to visualize the effect of shrinkage estimators and compare their performance to other estimators.\n\n## Recent Posts\n- [Successor project QHELP approved](https:\/\/tquant.eu\/successor-project-qhelp-approved\/) 10th July 2019\n- [TquanT Project Finished](https:\/\/tquant.eu\/tquant-project-finished\/) 1st September 2018\n- [Updated Privacy Statement](https:\/\/tquant.eu\/updated-privacy-statement\/) 26th May 2018\n- [Glasgow Apps Online](https:\/\/tquant.eu\/glasgow-apps-online\/) 19th April 2018\n\n## TquanT Shiny R Apps\n[Assumptions](https:\/\/tquant.eu\/tag\/assumptions\/)[Bayes](https:\/\/tquant.eu\/tag\/bayes\/)[Classical Test Theory](https:\/\/tquant.eu\/tag\/classical-test-theory\/)[Consortium App](https:\/\/tquant.eu\/tag\/consortium-app\/)[Generalizability](https:\/\/tquant.eu\/tag\/generalizability\/)[Intraclass Correlation](https:\/\/tquant.eu\/tag\/intraclass-correlation\/)[Item Response Theory](https:\/\/tquant.eu\/tag\/irt\/)[Knowledge Space Theory](https:\/\/tquant.eu\/tag\/knowledge-space-theory\/)[learnr Tutorial](https:\/\/tquant.eu\/tag\/learnr-tutorial\/)[Machine Learning](https:\/\/tquant.eu\/tag\/machine-learning\/)[Maximum Likelihood](https:\/\/tquant.eu\/tag\/maximum-likelihood\/)[Mixed Models](https:\/\/tquant.eu\/tag\/mixed-models\/)[Model Comparison](https:\/\/tquant.eu\/tag\/model-comparison\/)[Monte Carlo](https:\/\/tquant.eu\/tag\/monte-carlo\/)[Multisensory Input](https:\/\/tquant.eu\/tag\/multisensory-input\/)[Network Models](https:\/\/tquant.eu\/tag\/network-models\/)[Parameter Estimation](https:\/\/tquant.eu\/tag\/parameter-estimation\/)[Power](https:\/\/tquant.eu\/tag\/power\/)[Probability Theory](https:\/\/tquant.eu\/tag\/probability-theory\/)[Reproducibility](https:\/\/tquant.eu\/tag\/reproducibility\/)[Signal Detection Theory](https:\/\/tquant.eu\/tag\/signal-detection-theory\/)[Statistical Learning](https:\/\/tquant.eu\/tag\/statistical-learning\/)[Statistics](https:\/\/tquant.eu\/tag\/statistics\/)[Student App](https:\/\/tquant.eu\/tag\/student-app\/)[Student Presentation](https:\/\/tquant.eu\/tag\/student-presentation\/)[Utilities](https:\/\/tquant.eu\/tag\/utilities\/)\n\n© All rights reserved 2016 - 2019, TquanT Consortium  \nHosted by University of Graz, AUSTRIA  \n  \n[Legal Disclaimer](https:\/\/tquant.eu\/legal-disclaimer\/) \\| [Privacy Information](https:\/\/tquant.eu\/privacy-information)\n\nTquanT was co-funded by the Erasmus+ Programme of the European Commission [![csm\\_logo-erasmus-plus\\_327d13b53f.png](https:\/\/tquant.eu\/images\/csm_logo-erasmus-plus_327d13b53f.png)](https:\/\/ec.europa.eu\/programmes\/erasmus-plus\/node_en)\n\nThis website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. [Cookie settings]()[ACCEPT]()\n\nPrivacy & Cookies Policy\n\nClose\n\n#### Privacy Overview\nThis website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.\n\n[Necessary]()\n\nNecessary\n\nAlways Enabled\n\nNecessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.\n\n[Non-necessary]()\n\nNon-necessary\n\nAny cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.\n\n[SAVE & ACCEPT]()","attrs_readable_markdown":"[Skip to content](https:\/\/tquant.eu\/online-learning-contents\/shiny-r-apps\/james-stein-estimator\/#content)\n\n[![TqzanT Logo - Tools for Teaching Quantitative Thinking](https:\/\/tquant.eu\/wp-content\/uploads\/2016\/08\/tquant.png)](https:\/\/tquant.eu\/)\n\n- [TquanT](https:\/\/tquant.eu\/)\n  - [About TquanT](https:\/\/tquant.eu\/tquant\/about-tquant\/)\n  - [TquanT Consortium](https:\/\/tquant.eu\/tquant\/tquant-consortium\/)\n- [Mobilities](https:\/\/tquant.eu\/mobilities\/)\n  - [2016 – Lisbon](https:\/\/tquant.eu\/mobilities\/2016-lisbon\/)\n  - [2017 – Graz](https:\/\/tquant.eu\/mobilities\/2017-graz\/)\n    - [Programme](https:\/\/tquant.eu\/mobilities\/2017-graz\/programme\/)\n    - [Travel Information](https:\/\/tquant.eu\/mobilities\/2017-graz\/travel-information\/)\n  - [2018 – Glasgow](https:\/\/tquant.eu\/mobilities\/2018-glasgow\/)\n    - [Programme](https:\/\/tquant.eu\/mobilities\/2018-glasgow\/programme\/)\n    - [Preparation for the Seminar](https:\/\/tquant.eu\/mobilities\/2018-glasgow\/preparation\/)\n    - [Travel Information](https:\/\/tquant.eu\/mobilities\/2018-glasgow\/travel-information\/)\n  - [2019 – Balatonföldvär](https:\/\/tquant.eu\/mobilities\/2019-balatonfoldvar\/)\n    - [Programme](https:\/\/tquant.eu\/mobilities\/2019-balatonfoldvar\/programme\/)\n    - [Student Project Proposals](https:\/\/tquant.eu\/mobilities\/2019-balatonfoldvar\/student-project-proposals\/)\n- [Online Learning Contents](https:\/\/tquant.eu\/online-learning-contents\/)\n  - [Moodle Server](https:\/\/tquant.eu\/online-learning-contents\/moodle-server\/)\n  - [R Shiny Apps](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/)\n    - [Bayesian Statistics & Computation](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/bayesian-statistics-computation\/)\n    - [Knowledge Space Theory](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/knowledge-space-theory\/)\n    - [Multisensory Input](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/multisensory-input\/)\n    - [Probability Theory](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/probability-theory\/)\n    - [Model Comparison](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/model-comparison\/)\n    - [Miscellaneous Apps](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/miscellaneous-apps\/)\n    - [2016 Seminar](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/2016-seminar\/)\n    - [2017 Seminar](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/2017-seminar\/)\n    - [2018 Seminar](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/2018-seminar\/)\n    - [2019 Seminar](https:\/\/tquant.eu\/online-learning-contents\/r-shiny-apps\/2019-seminar\/)\n- [News](https:\/\/tquant.eu\/news\/)\n- [Contact](https:\/\/tquant.eu\/contact\/)\n\n- [Home](https:\/\/tquant.eu\/)\n- [Online Learning Contents](https:\/\/tquant.eu\/online-learning-contents\/)\n- [Shiny R Apps](https:\/\/tquant.eu\/online-learning-contents\/shiny-r-apps\/)\n- James-Stein estimator\n\n[![](https:\/\/tquant.eu\/wp-content\/uploads\/2017\/05\/James-Stein.png)](https:\/\/r.tquant.eu\/UvA\/JamesSteinEstimator\/)  \n The goal of this shiny app is to visualize the effect of shrinkage estimators and compare their performance to other estimators.\n\n- [Successor project QHELP approved](https:\/\/tquant.eu\/successor-project-qhelp-approved\/) 10th July 2019\n- [TquanT Project Finished](https:\/\/tquant.eu\/tquant-project-finished\/) 1st September 2018\n- [Updated Privacy Statement](https:\/\/tquant.eu\/updated-privacy-statement\/) 26th May 2018\n- [Glasgow Apps Online](https:\/\/tquant.eu\/glasgow-apps-online\/) 19th April 2018\n\n[Assumptions](https:\/\/tquant.eu\/tag\/assumptions\/)[Bayes](https:\/\/tquant.eu\/tag\/bayes\/)[Classical Test Theory](https:\/\/tquant.eu\/tag\/classical-test-theory\/)[Consortium App](https:\/\/tquant.eu\/tag\/consortium-app\/)[Generalizability](https:\/\/tquant.eu\/tag\/generalizability\/)[Intraclass Correlation](https:\/\/tquant.eu\/tag\/intraclass-correlation\/)[Item Response Theory](https:\/\/tquant.eu\/tag\/irt\/)[Knowledge Space Theory](https:\/\/tquant.eu\/tag\/knowledge-space-theory\/)[learnr Tutorial](https:\/\/tquant.eu\/tag\/learnr-tutorial\/)[Machine Learning](https:\/\/tquant.eu\/tag\/machine-learning\/)[Maximum Likelihood](https:\/\/tquant.eu\/tag\/maximum-likelihood\/)[Mixed Models](https:\/\/tquant.eu\/tag\/mixed-models\/)[Model Comparison](https:\/\/tquant.eu\/tag\/model-comparison\/)[Monte Carlo](https:\/\/tquant.eu\/tag\/monte-carlo\/)[Multisensory Input](https:\/\/tquant.eu\/tag\/multisensory-input\/)[Network Models](https:\/\/tquant.eu\/tag\/network-models\/)[Parameter Estimation](https:\/\/tquant.eu\/tag\/parameter-estimation\/)[Power](https:\/\/tquant.eu\/tag\/power\/)[Probability Theory](https:\/\/tquant.eu\/tag\/probability-theory\/)[Reproducibility](https:\/\/tquant.eu\/tag\/reproducibility\/)[Signal Detection Theory](https:\/\/tquant.eu\/tag\/signal-detection-theory\/)[Statistical Learning](https:\/\/tquant.eu\/tag\/statistical-learning\/)[Statistics](https:\/\/tquant.eu\/tag\/statistics\/)[Student App](https:\/\/tquant.eu\/tag\/student-app\/)[Student Presentation](https:\/\/tquant.eu\/tag\/student-presentation\/)[Utilities](https:\/\/tquant.eu\/tag\/utilities\/)\n\nThis website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. [Cookie settings]()[ACCEPT]()","meta_canonical":null}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📄

INDEXABLE

✅

CRAWLED

3 days ago

🤖

ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	0.1 months ago
History drop	PASS	`isNull(history_drop_reason)`	No drop reason
Spam/ban	PASS	`fh_dont_index != 1 AND ml_spam_score = 0`	ml_spam_score=0
Canonical	PASS	`meta_canonical IS NULL OR = '' OR = src_unparsed`	Not set

Page Details

Property	Value
URL	https://tquant.eu/online-learning-contents/shiny-r-apps/james-stein-estimator/
Last Crawled	2026-04-14 21:00:15 (3 days ago)
First Indexed	2017-10-25 06:25:33 (8 years ago)
HTTP Status Code	200
Meta Title	James-Stein estimator – Tools for Teaching Quantitative Thinking
Meta Description	null
Meta Canonical	null
Boilerpipe Text	Skip to content TquanT About TquanT TquanT Consortium Mobilities 2016 – Lisbon 2017 – Graz Programme Travel Information 2018 – Glasgow Programme Preparation for the Seminar Travel Information 2019 – Balatonföldvär Programme Student Project Proposals Online Learning Contents Moodle Server R Shiny Apps Bayesian Statistics & Computation Knowledge Space Theory Multisensory Input Probability Theory Model Comparison Miscellaneous Apps 2016 Seminar 2017 Seminar 2018 Seminar 2019 Seminar News Contact Home Online Learning Contents Shiny R Apps James-Stein estimator The goal of this shiny app is to visualize the effect of shrinkage estimators and compare their performance to other estimators. Successor project QHELP approved 10th July 2019 TquanT Project Finished 1st September 2018 Updated Privacy Statement 26th May 2018 Glasgow Apps Online 19th April 2018 Assumptions Bayes Classical Test Theory Consortium App Generalizability Intraclass Correlation Item Response Theory Knowledge Space Theory learnr Tutorial Machine Learning Maximum Likelihood Mixed Models Model Comparison Monte Carlo Multisensory Input Network Models Parameter Estimation Power Probability Theory Reproducibility Signal Detection Theory Statistical Learning Statistics Student App Student Presentation Utilities This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Cookie settings ACCEPT
Markdown	[Skip to content](https://tquant.eu/online-learning-contents/shiny-r-apps/james-stein-estimator/#content) [![TqzanT Logo - Tools for Teaching Quantitative Thinking](https://tquant.eu/wp-content/uploads/2016/08/tquant.png)](https://tquant.eu/) - [TquanT](https://tquant.eu/) - [About TquanT](https://tquant.eu/tquant/about-tquant/) - [TquanT Consortium](https://tquant.eu/tquant/tquant-consortium/) - [Mobilities](https://tquant.eu/mobilities/) - [2016 – Lisbon](https://tquant.eu/mobilities/2016-lisbon/) - [2017 – Graz](https://tquant.eu/mobilities/2017-graz/) - [Programme](https://tquant.eu/mobilities/2017-graz/programme/) - [Travel Information](https://tquant.eu/mobilities/2017-graz/travel-information/) - [2018 – Glasgow](https://tquant.eu/mobilities/2018-glasgow/) - [Programme](https://tquant.eu/mobilities/2018-glasgow/programme/) - [Preparation for the Seminar](https://tquant.eu/mobilities/2018-glasgow/preparation/) - [Travel Information](https://tquant.eu/mobilities/2018-glasgow/travel-information/) - [2019 – Balatonföldvär](https://tquant.eu/mobilities/2019-balatonfoldvar/) - [Programme](https://tquant.eu/mobilities/2019-balatonfoldvar/programme/) - [Student Project Proposals](https://tquant.eu/mobilities/2019-balatonfoldvar/student-project-proposals/) - [Online Learning Contents](https://tquant.eu/online-learning-contents/) - [Moodle Server](https://tquant.eu/online-learning-contents/moodle-server/) - [R Shiny Apps](https://tquant.eu/online-learning-contents/r-shiny-apps/) - [Bayesian Statistics & Computation](https://tquant.eu/online-learning-contents/r-shiny-apps/bayesian-statistics-computation/) - [Knowledge Space Theory](https://tquant.eu/online-learning-contents/r-shiny-apps/knowledge-space-theory/) - [Multisensory Input](https://tquant.eu/online-learning-contents/r-shiny-apps/multisensory-input/) - [Probability Theory](https://tquant.eu/online-learning-contents/r-shiny-apps/probability-theory/) - [Model Comparison](https://tquant.eu/online-learning-contents/r-shiny-apps/model-comparison/) - [Miscellaneous Apps](https://tquant.eu/online-learning-contents/r-shiny-apps/miscellaneous-apps/) - [2016 Seminar](https://tquant.eu/online-learning-contents/r-shiny-apps/2016-seminar/) - [2017 Seminar](https://tquant.eu/online-learning-contents/r-shiny-apps/2017-seminar/) - [2018 Seminar](https://tquant.eu/online-learning-contents/r-shiny-apps/2018-seminar/) - [2019 Seminar](https://tquant.eu/online-learning-contents/r-shiny-apps/2019-seminar/) - [News](https://tquant.eu/news/) - [Contact](https://tquant.eu/contact/) # James-Stein estimator - [Home](https://tquant.eu/) - [Online Learning Contents](https://tquant.eu/online-learning-contents/) - [Shiny R Apps](https://tquant.eu/online-learning-contents/shiny-r-apps/) - James-Stein estimator [![](https://tquant.eu/wp-content/uploads/2017/05/James-Stein.png)](https://r.tquant.eu/UvA/JamesSteinEstimator/) The goal of this shiny app is to visualize the effect of shrinkage estimators and compare their performance to other estimators. ## Recent Posts - [Successor project QHELP approved](https://tquant.eu/successor-project-qhelp-approved/) 10th July 2019 - [TquanT Project Finished](https://tquant.eu/tquant-project-finished/) 1st September 2018 - [Updated Privacy Statement](https://tquant.eu/updated-privacy-statement/) 26th May 2018 - [Glasgow Apps Online](https://tquant.eu/glasgow-apps-online/) 19th April 2018 ## TquanT Shiny R Apps [Assumptions](https://tquant.eu/tag/assumptions/)[Bayes](https://tquant.eu/tag/bayes/)[Classical Test Theory](https://tquant.eu/tag/classical-test-theory/)[Consortium App](https://tquant.eu/tag/consortium-app/)[Generalizability](https://tquant.eu/tag/generalizability/)[Intraclass Correlation](https://tquant.eu/tag/intraclass-correlation/)[Item Response Theory](https://tquant.eu/tag/irt/)[Knowledge Space Theory](https://tquant.eu/tag/knowledge-space-theory/)[learnr Tutorial](https://tquant.eu/tag/learnr-tutorial/)[Machine Learning](https://tquant.eu/tag/machine-learning/)[Maximum Likelihood](https://tquant.eu/tag/maximum-likelihood/)[Mixed Models](https://tquant.eu/tag/mixed-models/)[Model Comparison](https://tquant.eu/tag/model-comparison/)[Monte Carlo](https://tquant.eu/tag/monte-carlo/)[Multisensory Input](https://tquant.eu/tag/multisensory-input/)[Network Models](https://tquant.eu/tag/network-models/)[Parameter Estimation](https://tquant.eu/tag/parameter-estimation/)[Power](https://tquant.eu/tag/power/)[Probability Theory](https://tquant.eu/tag/probability-theory/)[Reproducibility](https://tquant.eu/tag/reproducibility/)[Signal Detection Theory](https://tquant.eu/tag/signal-detection-theory/)[Statistical Learning](https://tquant.eu/tag/statistical-learning/)[Statistics](https://tquant.eu/tag/statistics/)[Student App](https://tquant.eu/tag/student-app/)[Student Presentation](https://tquant.eu/tag/student-presentation/)[Utilities](https://tquant.eu/tag/utilities/) © All rights reserved 2016 - 2019, TquanT Consortium Hosted by University of Graz, AUSTRIA [Legal Disclaimer](https://tquant.eu/legal-disclaimer/) \\| [Privacy Information](https://tquant.eu/privacy-information) TquanT was co-funded by the Erasmus+ Programme of the European Commission [![csm\_logo-erasmus-plus\_327d13b53f.png](https://tquant.eu/images/csm_logo-erasmus-plus_327d13b53f.png)](https://ec.europa.eu/programmes/erasmus-plus/node_en) This website uses cookies to improve your experience. 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