Spatio-temporal prediction of the population size at Tehran urban areas using BirnbaumSaunders Markov random fields

Spatio-temporal prediction of the population size at Tehran urban areas using BirnbaumSaunders Markov random fields | 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 Research Article Spatio-temporal prediction of the population size at Tehran urban areas using BirnbaumSaunders Markov random fields Majid Jafari Khaledi, Sara Bourbour, Helia Safarkhanloo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-958268/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 For implementing an intelligent urban management, it is necessary and inevitable to know the population size in different areas of Tehran city and identify how they change over time. Population and housing census data can determine the spatio-temporal distribution of the people and how it evolves. However, census will not be implemented across the country in 2021, like a previous manner, due to issues related to the coronavirus pandemic and its prevalence. From this perspective, the prediction of the population size is significant in different regions of Tehran for the year 2021. This paper focuses on developing a statistical learning model for predicting the population growth rate of Tehran urban areas. To be more specific, since the growth rates data are spatially correlated, skewed to the right, and positive, a Birnbaum- Saunders Markov random field (BSMRF) is proposed. We adopt a Bayesian framework for the parameter estimation and spatial prediction and use Markov chain Monte Carlo methods to sample from the posterior distribution. Then, the results are compared with the traditional models. Environmental Chemistry Environmental Engineering Skewed spatial data Birnbaum-Saunders distribution Markov random field Population rate Census data Bayesian Inference Full Text 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-958268","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":56349115,"identity":"64d0b433-8cc0-42ff-90ae-9dd7b8bff6a9","order_by":0,"name":"Majid Jafari Khaledi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYBACxgbGBwwMBgwM/ECOBFw4Aa8WZgOwFskGYrUwMIC0AIHBAWQteDW0H2b8XFHAEG187fDBGz/32NgzsB9+wPBwDx6H9SQzS54xYMjddjst2bLnWVpiA0+aAUPCM3x+yT8g2WDwH6glx0yC58BhoC9ygH45gEdL/2Pmnw1AWzbPzjGT/HPgvz0D/xsCWmYks0mCtGyQzjGT5jlwgLFBgpAtMx6zWYK0zAD6xVrmQHJim8QzgwP4tBj2JzPfbPjDkNs/O/ngzTcH7Oz5+ZMfPvyBT0sDuggbEOPRwMAgj09yFIyCUTAKRgEYAADw81BlrY/FowAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-2138-1098","institution":"Tarbiat Modares University","correspondingAuthor":true,"prefix":"","firstName":"Majid","middleName":"Jafari","lastName":"Khaledi","suffix":""},{"id":56349116,"identity":"5299958b-7614-4817-a7b0-894676adc558","order_by":1,"name":"Sara Bourbour","email":"","orcid":"","institution":"Tehran Center for Urban Statistics and Observatory","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Bourbour","suffix":""},{"id":56349117,"identity":"302c2e27-b50f-44e9-849c-4c2401df9c43","order_by":2,"name":"Helia Safarkhanloo","email":"","orcid":"","institution":"Tehran Center for Urban Statistics and Observatory","correspondingAuthor":false,"prefix":"","firstName":"Helia","middleName":"","lastName":"Safarkhanloo","suffix":""}],"badges":[],"createdAt":"2021-10-06 23:56:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-958268/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-958268/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":14553580,"identity":"7162a4f5-c4fb-448e-b9e8-ac0d52e2ea7b","added_by":"auto","created_at":"2021-10-15 14:31:16","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":351087,"visible":true,"origin":"","legend":"","description":"","filename":"Paper.pdf","url":"https://assets-eu.researchsquare.com/files/rs-958268/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"Spatio-temporal prediction of the population size at Tehran urban areas using BirnbaumSaunders Markov random fields","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-958268/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"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":"Skewed spatial data, Birnbaum-Saunders distribution, Markov random field, Population rate, Census data, Bayesian Inference","lastPublishedDoi":"10.21203/rs.3.rs-958268/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-958268/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"For implementing an intelligent urban management, it is necessary and inevitable to know the population size in different areas of Tehran city and identify how they change over time. 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