{"id":118,"date":"2016-09-04T22:01:34","date_gmt":"2016-09-04T22:01:34","guid":{"rendered":"http:\/\/jsr.isrt.ac.bd\/?post_type=article&#038;p=118"},"modified":"2016-09-06T02:19:02","modified_gmt":"2016-09-06T02:19:02","slug":"l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles","status":"publish","type":"article","link":"http:\/\/jsr.isrt.ac.bd\/article\/l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles\/","title":{"rendered":"L-estimation of the parameters in a linear model based on a few selected regression quantiles"},"content":{"rendered":"<p>This paper considers the L-estimation of regression and scale parameter of the linear model\u00a0Y = 01o + X + e, where 0 is the intercept parameters and is the scale in the\u00a0model, based on k( n) optimum regression quantiles as defined by Koenker and Bassett\u00a0(1978). In addition, the paper contains the trimmed estimation problem with continuous\u00a0weight functions, the estimation of conditional regression function and the related \u00a0optimum\u00a0regression quantiles.<\/p>\n<p><a href=\"http:\/\/jsr.isrt.ac.bd\/wp-content\/uploads\/47n1_8.pdf\">Fulltext<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper considers the L-estimation of regression and scale parameter of the linear model\u00a0Y = 01o + X + e, where 0 is the intercept parameters and is the scale in the\u00a0model, based on k( n) optimum regression quantiles as defined by Koenker and Bassett\u00a0(1978). In addition, the paper contains the trimmed estimation problem with [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"menu_order":0,"comment_status":"open","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":[2],"issuem_issue_categories":[],"issuem_issue_tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>L-estimation of the parameters in a linear model based on a few selected regression quantiles - 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\/l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"L-estimation of the parameters in a linear model based on a few selected regression quantiles - JSR\" \/>\n<meta property=\"og:description\" content=\"This paper considers the L-estimation of regression and scale parameter of the linear model\u00a0Y = 01o + X + e, where 0 is the intercept parameters and is the scale in the\u00a0model, based on k( n) optimum regression quantiles as defined by Koenker and Bassett\u00a0(1978). In addition, the paper contains the trimmed estimation problem with [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jsr.isrt.ac.bd\/article\/l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles\/\" \/>\n<meta property=\"og:site_name\" content=\"JSR\" \/>\n<meta property=\"article:modified_time\" content=\"2016-09-06T02:19:02+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles\/\",\"url\":\"https:\/\/jsr.isrt.ac.bd\/article\/l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles\/\",\"name\":\"L-estimation of the parameters in a linear model based on a few selected regression quantiles - JSR\",\"isPartOf\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/#website\"},\"datePublished\":\"2016-09-04T22:01:34+00:00\",\"dateModified\":\"2016-09-06T02:19:02+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/jsr.isrt.ac.bd\/article\/l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/jsr.isrt.ac.bd\/article\/l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles\/#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\":\"L-estimation of the parameters in a linear model based on a few selected regression quantiles\"}]},{\"@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":"L-estimation of the parameters in a linear model based on a few selected regression quantiles - 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\/l-estimation-of-the-parameters-in-a-linear-model-based-on-a-few-selected-regression-quantiles\/","og_locale":"en_US","og_type":"article","og_title":"L-estimation of the parameters in a linear model based on a few selected regression quantiles - JSR","og_description":"This paper considers the L-estimation of regression and scale parameter of the linear model\u00a0Y = 01o + X + e, where 0 is the intercept parameters and is the scale in the\u00a0model, based on k( n) optimum regression quantiles as defined by Koenker and Bassett\u00a0(1978). 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