{"id":763,"date":"2019-03-11T03:35:55","date_gmt":"2019-03-11T03:35:55","guid":{"rendered":"http:\/\/jsr.isrt.ac.bd\/?post_type=article&#038;p=763"},"modified":"2020-09-28T19:36:48","modified_gmt":"2020-09-28T19:36:48","slug":"estimating-variance-mean-mixtures-of-normals","status":"publish","type":"article","link":"http:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/","title":{"rendered":"Estimating variance-mean mixtures of Normals"},"content":{"rendered":"<p class=\"p1\">A new semi-nonparametric method for modeling data with Normal variance-mean mixtures (NVMM) is presented. This new method is based on the least-squares programming routine, UNMIX. Density estimates based on random samples of size n from two, three, and four components of NVMM are found using UNMIX. Graphical comparisons of the UNMIX fit found by the EM Algorithm and the Bayesian approaches are done using three real life examples. A quantitative comparison using the AIC and Chi-Square is done for one of the most commonly used examples, the Galaxy Data. The results are promising and the method has great potential for improvement.<\/p>\n<p><a href=\"http:\/\/jsr.isrt.ac.bd\/wp-content\/uploads\/52n2_2.pdf\">Fulltext: <\/a><a href=\"https:\/\/doi.org\/10.47302\/jsr.2018520202\">https:\/\/doi.org\/10.47302\/jsr.2018520202<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A new semi-nonparametric method for modeling data with Normal variance-mean mixtures (NVMM) is presented. This new method is based on the least-squares programming routine, UNMIX. Density estimates based on random samples of size n from two, three, and four components of NVMM are found using UNMIX. Graphical comparisons of the UNMIX fit found by the [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"issuem_issue":[24],"issuem_issue_categories":[],"issuem_issue_tags":[],"class_list":["post-763","article","type-article","status-publish","format-standard","hentry","issuem_issue-v52n2"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Estimating variance-mean mixtures of Normals - JSR<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Estimating variance-mean mixtures of Normals - JSR\" \/>\n<meta property=\"og:description\" content=\"A new semi-nonparametric method for modeling data with Normal variance-mean mixtures (NVMM) is presented. This new method is based on the least-squares programming routine, UNMIX. Density estimates based on random samples of size n from two, three, and four components of NVMM are found using UNMIX. Graphical comparisons of the UNMIX fit found by the [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/\" \/>\n<meta property=\"og:site_name\" content=\"JSR\" \/>\n<meta property=\"article:modified_time\" content=\"2020-09-28T19:36:48+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/\",\"url\":\"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/\",\"name\":\"Estimating variance-mean mixtures of Normals - JSR\",\"isPartOf\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/#website\"},\"datePublished\":\"2019-03-11T03:35:55+00:00\",\"dateModified\":\"2020-09-28T19:36:48+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/jsr.isrt.ac.bd\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Articles\",\"item\":\"https:\/\/jsr.isrt.ac.bd\/article\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Estimating variance-mean mixtures of Normals\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/#website\",\"url\":\"https:\/\/jsr.isrt.ac.bd\/\",\"name\":\"JSR\",\"description\":\"Journal of Statistical Research\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/jsr.isrt.ac.bd\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Estimating variance-mean mixtures of Normals - JSR","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/","og_locale":"en_US","og_type":"article","og_title":"Estimating variance-mean mixtures of Normals - JSR","og_description":"A new semi-nonparametric method for modeling data with Normal variance-mean mixtures (NVMM) is presented. This new method is based on the least-squares programming routine, UNMIX. Density estimates based on random samples of size n from two, three, and four components of NVMM are found using UNMIX. Graphical comparisons of the UNMIX fit found by the [&hellip;]","og_url":"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/","og_site_name":"JSR","article_modified_time":"2020-09-28T19:36:48+00:00","twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/","url":"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/","name":"Estimating variance-mean mixtures of Normals - JSR","isPartOf":{"@id":"https:\/\/jsr.isrt.ac.bd\/#website"},"datePublished":"2019-03-11T03:35:55+00:00","dateModified":"2020-09-28T19:36:48+00:00","breadcrumb":{"@id":"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/jsr.isrt.ac.bd\/article\/estimating-variance-mean-mixtures-of-normals\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/jsr.isrt.ac.bd\/"},{"@type":"ListItem","position":2,"name":"Articles","item":"https:\/\/jsr.isrt.ac.bd\/article\/"},{"@type":"ListItem","position":3,"name":"Estimating variance-mean mixtures of Normals"}]},{"@type":"WebSite","@id":"https:\/\/jsr.isrt.ac.bd\/#website","url":"https:\/\/jsr.isrt.ac.bd\/","name":"JSR","description":"Journal of Statistical Research","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/jsr.isrt.ac.bd\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"}]}},"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/article\/763","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/article"}],"about":[{"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/types\/article"}],"author":[{"embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/comments?post=763"}],"version-history":[{"count":0,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/article\/763\/revisions"}],"wp:attachment":[{"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/media?parent=763"}],"wp:term":[{"taxonomy":"issuem_issue","embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/issuem_issue?post=763"},{"taxonomy":"issuem_issue_categories","embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/issuem_issue_categories?post=763"},{"taxonomy":"issuem_issue_tags","embeddable":true,"href":"http:\/\/jsr.isrt.ac.bd\/wp-json\/wp\/v2\/issuem_issue_tags?post=763"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}