{"id":394,"date":"2020-08-21T22:42:19","date_gmt":"2020-08-21T22:42:19","guid":{"rendered":"https:\/\/lorandparajdi.wordpress.com\/?page_id=394"},"modified":"2023-07-17T15:50:18","modified_gmt":"2023-07-17T15:50:18","slug":"covid-19-data-fitting-with-linear-and-nonlinear-regression","status":"publish","type":"page","link":"https:\/\/www.cs.ubbcluj.ro\/~lorand\/covid-19-data-fitting-with-linear-and-nonlinear-regression\/","title":{"rendered":"Soft package no.1"},"content":{"rendered":"\n<p class=\"has-text-align-center\" style=\"font-size:28px\">COVID-19 Data Fitting with Linear and Nonlinear Regression<a style=\"display:block; font-size:13px; line-height:3.5em; color:#555555;\">Matlab Package, April 15, 2020 \/ Lorand Gabriel Parajdi<\/a><\/p>\n\n\n\n<p style=\"font-size:15px\">Published at MATLAB Central File Exchange <a rel=\"noreferrer noopener\" href=\"https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/75016-covid19-data-fitting-with-linear-and-nonlinear-regression\" target=\"_blank\"><span class=\"has-inline-color has-vivid-cyan-blue-color\">https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/75016-covid19-data-fitting-with-linear-and-nonlinear-regression.<\/span><\/a><\/p>\n\n\n\n<p style=\"font-size:15px\"><strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-black-color\">Authors:<\/mark><\/strong> Lorand Gabriel Parajdi<sup>1<\/sup> and Ioan Stefan Haplea<sup>2<\/sup> <\/p>\n\n\n\n<p style=\"font-size:15px\"><a style=\"display:block; color:#474747;\"><sup>1 <\/sup>Department of Mathematics, &#8220;Babe\u015f\u2013Bolyai&#8221; University, Cluj-Napoca, Romania<\/a><sup>2<\/sup> Department of Internal Medicine, &#8220;Iuliu Ha\u021bieganu&#8221; University of Medicine and Pharmacy, Cluj-Napoca, Romania<\/p>\n\n\n\n<p style=\"font-size:15px\"><strong><span class=\"has-inline-color has-black-color\">Abstract:<\/span><\/strong>  A collection of tools for fitting several general-purpose linear and nonlinear models for COVID-19 epidemiological data. The longitudinal data is obtained from the John Hopkins database (source:&nbsp;<a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/CSSEGISandData\/COVID-19\" target=\"_blank\"><span class=\"has-inline-color has-vivid-cyan-blue-color\">https:\/\/github.com\/CSSEGISandData\/COVID-19<\/span><\/a>) and consists of: number of active cases, number of confirmed, number of fatalities, number of recovered cases. The analysis is possible for any particular country listed in the database, or for the world data as a whole. The models implemented include linear, exponential, logistic, Gompertz, fifth-degree polynomial, Gaussians and Fourier functions. The three models of the Bertalanffy class (exponential, proper logistic and Gompertz) afford a reasonable balance between reduced model complexity and goodness of fit. We implement data\/model visualization in linear and logarithmic scales, for easy model comparisons.<\/p>\n\n\n\n<p style=\"font-size:15px\"><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-black-color\"><strong>Keywords<\/strong>:<\/mark>  Coronavirus; Covid19; Data fitting; Epidemiology; Exponential; Fourier; Gaussian; Gompertz; Linear; Logistic; Linear; Pandemic; Regression<\/p>\n\n\n\n<p class=\"has-black-color has-text-color\" style=\"font-size:15px\"><strong><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-black-color\">Cite As:<\/mark><\/strong>  Lorand Gabriel Parajdi and Ioan Stefan Haplea (2020). COVID-19 Data Fitting with Linear and Nonlinear Regression (https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/75016-covid19-data-fitting-with-linear-and-nonlinear-regression), MATLAB Central File Exchange. Retrieved April 15, 2020.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>COVID-19 Data Fitting with Linear and Nonlinear RegressionMatlab Package, April 15, 2020 \/ Lorand Gabriel Parajdi Published at MATLAB Central File Exchange https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/75016-covid19-data-fitting-with-linear-and-nonlinear-regression. Authors: Lorand Gabriel Parajdi1 and Ioan Stefan Haplea2 1 Department of Mathematics, &#8220;Babe\u015f\u2013Bolyai&#8221; University, Cluj-Napoca, Romania2 Department of Internal Medicine, &#8220;Iuliu Ha\u021bieganu&#8221; University of Medicine and Pharmacy, Cluj-Napoca, Romania Abstract: A collection &hellip; <a href=\"https:\/\/www.cs.ubbcluj.ro\/~lorand\/covid-19-data-fitting-with-linear-and-nonlinear-regression\/\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">Soft package no.1<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~lorand\/wp-json\/wp\/v2\/pages\/394"}],"collection":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~lorand\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~lorand\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~lorand\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~lorand\/wp-json\/wp\/v2\/comments?post=394"}],"version-history":[{"count":30,"href":"https:\/\/www.cs.ubbcluj.ro\/~lorand\/wp-json\/wp\/v2\/pages\/394\/revisions"}],"predecessor-version":[{"id":5404,"href":"https:\/\/www.cs.ubbcluj.ro\/~lorand\/wp-json\/wp\/v2\/pages\/394\/revisions\/5404"}],"wp:attachment":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~lorand\/wp-json\/wp\/v2\/media?parent=394"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}