{"id":605,"date":"2017-09-28T05:04:00","date_gmt":"2017-09-28T05:04:00","guid":{"rendered":"http:\/\/jsr.isrt.ac.bd\/?post_type=article&#038;p=605"},"modified":"2017-09-28T05:04:07","modified_gmt":"2017-09-28T05:04:07","slug":"comparing-ratio-estimators-based-systematic-samples","status":"publish","type":"article","link":"http:\/\/jsr.isrt.ac.bd\/article\/comparing-ratio-estimators-based-systematic-samples\/","title":{"rendered":"Comparing ratio estimators based on systematic samples"},"content":{"rendered":"<p>The purpose of this study is to evaluate competitive ratio estimators, and introduce<br \/>\na new approach to estimation when a systematic sample of size <img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/jsr.isrt.ac.bd\/wp-content\/ql-cache\/quicklatex.com-a63eb5ff0272d3119fa684be6e7acce8_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#110;\" title=\"Rendered by QuickLaTeX.com\" height=\"8\" width=\"11\" style=\"vertical-align: 0px;\"\/> with<br \/>\na random start is used. The competitive ratio estimators are the mean of ratios,<br \/>\nratio of means, and the conditional best linear unbiased estimator. These<br \/>\nestimators are used to measure the population proportion of the total of a variable<br \/>\n<img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/jsr.isrt.ac.bd\/wp-content\/ql-cache\/quicklatex.com-ab67eda06fcf093fb3178b85c9214045_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#89;\" title=\"Rendered by QuickLaTeX.com\" height=\"12\" width=\"14\" style=\"vertical-align: 0px;\"\/> with respect to another variable, <img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/jsr.isrt.ac.bd\/wp-content\/ql-cache\/quicklatex.com-2453362c766504f3c3806fed710a5337_l3.png\" class=\"ql-img-inline-formula quicklatex-auto-format\" alt=\"&#88;\" title=\"Rendered by QuickLaTeX.com\" height=\"12\" width=\"16\" style=\"vertical-align: 0px;\"\/>. A new approach is suggested, a<br \/>\nbootstrap estimate using a non-linear additive regression technique, in which a<br \/>\nMonte-Carlo simulation is done using the predicted values from the fitted model<br \/>\nto find estimates for the variances. This new approach has yielded small mean<br \/>\nsquare errors.<\/p>\n<p><a href=\"http:\/\/jsr.isrt.ac.bd\/wp-content\/uploads\/40n2_1.pdf\">Fulltext<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The purpose of this study is to evaluate competitive ratio estimators, and introduce a new approach to estimation when a systematic sample of size with a random start is used. The competitive ratio estimators are the mean of ratios, ratio of means, and the conditional best linear unbiased estimator. These estimators are used to measure [&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":[19],"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>Comparing ratio estimators based on systematic samples - 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\/comparing-ratio-estimators-based-systematic-samples\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Comparing ratio estimators based on systematic samples - JSR\" \/>\n<meta property=\"og:description\" content=\"The purpose of this study is to evaluate competitive ratio estimators, and introduce a new approach to estimation when a systematic sample of size with a random start is used. The competitive ratio estimators are the mean of ratios, ratio of means, and the conditional best linear unbiased estimator. 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The competitive ratio estimators are the mean of ratios, ratio of means, and the conditional best linear unbiased estimator. 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