On Estimation of P(Y Ibn Al-Haitham Journal For Pure And Applied Science Pub Date : 2020-01-20 DOI:10.30526/33.1.2375 Bsma Abdul Hameed, A. N. Salman, B. A. Kalaf 求助PDF {"title":"On Estimation of P(Y<X) in Case Inverse Kumaraswamy Distribution","authors":"Bsma Abdul Hameed, A. N. Salman, B. A. Kalaf","doi":"10.30526/33.1.2375","DOIUrl":null,"url":null,"abstract":"The estimation of the stressـ strength reliability of Invers Kumaraswamy distribution will be introduced in this paper based on the maximum likelihood, moment and shrinkage methods. The mean squared error has been used to compare among proposed estimators. Also a Monte Carlo simulation study is conducted to investigate the performance of the proposed methods in this paper.","PeriodicalId":13236,"journal":{"name":"Ibn Al-Haitham Journal For Pure And Applied Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ibn Al-Haitham Journal For Pure And Applied Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30526/33.1.2375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0} 引用次数: 3 引用 批量引用 Abstract The estimation of the stressـ strength reliability of Invers Kumaraswamy distribution will be introduced in this paper based on the maximum likelihood, moment and shrinkage methods. The mean squared error has been used to compare among proposed estimators. Also a Monte Carlo simulation study is conducted to investigate the performance of the proposed methods in this paper. 分享 查看原文 本刊更多论文 逆Kumaraswamy分布中P(Y 本文介绍了基于极大似然法、弯矩法和收缩法的Kumaraswamy分布应力强度可靠度的估计。均方误差被用来比较所提出的估计量。通过蒙特卡罗仿真研究，验证了本文提出的方法的性能。 本文章由计算机程序翻译，如有差异，请以英文原文为准。 求助全文 约1分钟内获得全文 求助全文 来源期刊 Ibn Al-Haitham Journal For Pure And Applied Science 自引率 0.00% 发文量 0 相关文献 × 引用 GB/T 7714-2015 复制 MLA 复制 APA 复制 导出至 BibTeX EndNote RefMan NoteFirst NoteExpress × 求助内容： 期刊论文 学位论文 图书 其他 (专利、报告等) 只需要正文 仅需补充材料 应助结果提醒方式： 微信（请自行确认已关注Book学术公众号） 邮件 保存 保存后同步修改账户信息中的邮箱 确认发布求助 × 处理提示 您的部分求助已有人上传文件，您还尚未处理，请先处理完毕再发起新的求助 点击查看 × 努力提交中 提交成功 继续求助查看详情 × 提示 您的信息不完整，为了账户安全，请先补充。 现在去补充 × 没积分了 多种获得积分方式，供你选择！ 查看如何获取积分 × 提示 您因"违规操作" 具体请查看互助需知 我知道了 × 提示 现在去查看 取消 × 提示 确定 × 快捷登录 密码登录 用户名： 密码： 验证码： 两周内记住我 忘记密码？ 手机号： 验证码： 没有帐号？现在注册 请完成安全验证× 微信好友 朋友圈 QQ好友 复制链接 取消 已复制链接 快去分享给好友吧! 我知道了 点击右上角分享 0 $(function () { var title = $("#title").val(); var id = $("#id").val(); $.post("/Literature/GetRelatedLiterature", { id: id, title: title }, function (result) { if (result != null) { var html = ``; for (var i = 0; i < result.length; i++) { html += `<div class="sslist">`; html += `<a class="caption" href="` + $("#url1").val() + result[i].ArticleID + `.htm">` + result[i].Title + `</a>`; html += ` <div class="substance">`; html += `<span class="IF">IF ` + result[i].PeriodicalIF + ` </span>`; if (result[i].RegionNum > 0) { html += `<span class="fq` + result[i].RegionNum + `">` + result[i].RegionNum + `区 ` + result[i].RegionCategory + `</span>`; } //var EmployDataBaseShoreName = result[i].EmployDataBaseShoreName; //if (EmployDataBaseShoreName != "" && EmployDataBaseShoreName!=null) { // var names = EmployDataBaseShoreName.split('||') // for (var j = 0; j < names.length; j++) { // html += `<span class="fq5">` + names[j] + `</span>`; // } //} //html += ``; html += `</div>`; html += `<div class="substance">`; html += `<a href="` + $("#url2").val() + "_d" + result[i].PeriodicalID + `.htm" target="_blank">` + result[i].PeriodicalName + `</a>`; html += `<span class="Pub">Pub Date : ` + result[i].PublishDate + `</span>`; html += `</div>`; html += ` <div class="author">`; html += result[i].AuthorName; html += `</div>`; html += `</div>`; } if (html.length > 0) { $("#xglist").show(); $("#xglist").append(html); } } }); getReferenceCount(); }); function getReferenceCount() { var LocalId = localStorage.getItem("referenceName"); if (LocalId != null) { $.get("/Literature/GetBatchReferenceCountByLocalId", { LocalId: LocalId }, function (result) { $("#referencecount").html(result.Code); }, "json"); } else { $("#referencecount").html('0'); } } wx.config({ debug: false, appId: 'wx999b2eb01732df2e', timestamp: '1727901010', nonceStr: 'E6MI4QTkmWWuJYLz', signature: '6916ae207dcb0f433dcf83e3fdd6d2e8d5496a18', jsApiList: [ 'onMenuShareTimeline', 'onMenuShareAppMessage', 'hideMenuItems' ] });

Abstract

The estimation of the stressـ strength reliability of Invers Kumaraswamy distribution will be introduced in this paper based on the maximum likelihood, moment and shrinkage methods. The mean squared error has been used to compare among proposed estimators. Also a Monte Carlo simulation study is conducted to investigate the performance of the proposed methods in this paper.