infotest: Information Matrix Test for Linear Regression Models in R

infotest: Information Matrix Test for Linear Regression Models in R | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Method Article infotest: Information Matrix Test for Linear Regression Models in R Hasraddin Guliyev This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7898663/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This article introduces the infotest package for R, which implements the Information Matrix (IM) test for linear regression models. The IM test, originally proposed by White (1982) and later decomposed by Cameron and Trivedi (1990), provides a comprehensive diagnostic tool for assessing model misspecification. Building on the results of Chesher (1983) and Lancaster (1984), the test examines whether the information matrix equality holds–a fundamental property of correctly specified maximum likelihood models. The decomposition into heteroskedasticity, skewness, and kurtosis components allows researchers to identify specific sources of misspecification. Unlike unconditional normality tests, the IM test provides conditional moment testing that accounts for covariate patterns. The packagealsoincludes White’s classic heteroskedasticityt est (White1980) as a special case. We demonstrate the implementation through theoretical background, computational details, and practical examples. Applied Statistics information matrix test regression diagnostics heteroskedasticity skewness kur tosis conditional moments R. Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7898663","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Method Article","associatedPublications":[],"authors":[{"id":531866594,"identity":"7136c99e-ca34-4d39-a0bc-faacd945942c","order_by":0,"name":"Hasraddin Guliyev","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYBACAzDJxszDwMB8ACqWQLQWNphSIrUACR4D4rSYsx9/9uFHmbWMOf+ab9IFFXYM/Ow5Bgw//uDWYtmTYzyz51w6j+WMt9ukZ5xJZpDseWPA2MODx2EHcpgZeNsO8xjcOLtNmrftAIPBDaAtPBJ4tJx//pjxL1jLmWfSvP8OMNgDtTD+McCj5UaCMTPYlvM9bNK8DUBbJHIMmHnwBIHBjTfGzDJAvxjcYDO25jmWzCNx5lnBYZkD+ByW/pjxTZm1vcH5ww9v89TYyfG3J298+AZPiCGABMQt4KDCYwcy4CdS3SgYBaNgFIw8AAC4+E3HXNn3CwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-8192-0401","institution":"Azerbaijan State University of Economics","correspondingAuthor":true,"prefix":"","firstName":"Hasraddin","middleName":"","lastName":"Guliyev","suffix":""}],"badges":[],"createdAt":"2025-10-19 12:57:54","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7898663/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7898663/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":93980305,"identity":"fcd2e056-6250-4b81-aa64-ec22e96eef39","added_by":"auto","created_at":"2025-10-21 02:36:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":237926,"visible":true,"origin":"","legend":"","description":"","filename":"infotest.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7898663/v1_covered_cc20c2ce-0af6-45a6-84db-6f4dddb6be74.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003einfotest: Information Matrix Test for Linear Regression Models in R\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Azerbaijan State University of Economics","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"information matrix test, regression diagnostics, heteroskedasticity, skewness, kur tosis, conditional moments, R.","lastPublishedDoi":"10.21203/rs.3.rs-7898663/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7898663/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis article introduces the infotest package for R, which implements the Information Matrix (IM) test for linear regression models. 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