<?xml version="1.0" encoding="utf-8"?>
<journal>
<title>Mathematical Researches</title>
<title_fa>پژوهش های ریاضی</title_fa>
<short_title>mmr</short_title>
<subject>Basic Sciences</subject>
<web_url>http://mmr.khu.ac.ir</web_url>
<journal_hbi_system_id>1</journal_hbi_system_id>
<journal_hbi_system_user>admin</journal_hbi_system_user>
<journal_id_issn>2588-2546</journal_id_issn>
<journal_id_issn_online>2588-2554</journal_id_issn_online>
<journal_id_pii></journal_id_pii>
<journal_id_doi>10.61186/mmr</journal_id_doi>
<journal_id_iranmedex></journal_id_iranmedex>
<journal_id_magiran></journal_id_magiran>
<journal_id_sid></journal_id_sid>
<journal_id_nlai></journal_id_nlai>
<journal_id_science></journal_id_science>
<language>fa</language>
<pubdate>
	<type>jalali</type>
	<year>1401</year>
	<month>3</month>
	<day>1</day>
</pubdate>
<pubdate>
	<type>gregorian</type>
	<year>2022</year>
	<month>6</month>
	<day>1</day>
</pubdate>
<volume>8</volume>
<number>2</number>
<publish_type>online</publish_type>
<publish_edition>1</publish_edition>
<article_type>fulltext</article_type>
<articleset>
	<article>


	<language>fa</language>
	<article_id_doi></article_id_doi>
	<title_fa>بهینه سازی اندازه نمونه تصادفی در سانسور فزاینده نوع دو برمبنای معیار هزینه</title_fa>
	<title>Optimization of Random Sample Size in Progressively Type II Censoring based on Cost Criterion</title>
	<subject_fa>آمار</subject_fa>
	<subject>Stat</subject>
	<content_type_fa>علمی پژوهشی بنیادی</content_type_fa>
	<content_type>S</content_type>
	<abstract_fa>نمونه &amp;shy;های سانسور شده تاکنون توسط پژوهش&amp;shy;گران زیادی مورد مطالعه قرار گرفته&amp;shy; اند. یکی از مهم&amp;shy;ترین روش&amp;shy;های سانسور، سانسور فزاینده نوع دو است. یکی از مسائلی که در بحث سانسورها مطرح است تعیین اندازه نمونه مناسب است. برای تعیین اندازه نمونه مناسب عوامل مختلفی تاثیرگذار هستند که از مهم&amp;shy;ترین عوامل می&amp;shy; توان به معیار هزینه نمونه&amp;shy; گیری اشاره کرد. در این مقاله، با فرض اینکه اندازه نمونه متغیری تصادفی از توزیع دوجمله &amp;shy;ای باشد، به تعیین پارامتر بهینه توزیع اندازه نمونه در سانسور فزاینده نوع دو پرداخته می&amp;shy; شود. این پارامتر بهینه طوری تعیین می&amp;shy; شود که مقدار هزینه کل آزمایش از مقدار از قبل تعیین شده&amp;shy; ای بیشتر نشود. در این مقاله توزیع نمایی برای توزیع مشاهدات در نظر گرفته شده است. برای ارزیابی نتایج بدست آمده مطالعه شبیه&amp;shy; سازی نیز انجام شده است. در پایان نتیجه&amp;shy; گیری از مقاله ارائه شده است. &amp;nbsp;</abstract_fa>
	<abstract>&lt;span style=&quot;font-size:12pt&quot;&gt;&lt;span style=&quot;line-height:22.0pt&quot;&gt;&lt;span new=&quot;&quot; roman=&quot;&quot; style=&quot;font-family:&quot; times=&quot;&quot;&gt;&lt;b&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;&lt;span new=&quot;&quot; roman=&quot;&quot; style=&quot;font-family:&quot; times=&quot;&quot;&gt;Introduction&lt;/span&gt;&lt;/span&gt;&lt;/b&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:11pt&quot;&gt;&lt;span style=&quot;line-height:17.0pt&quot;&gt;&lt;span style=&quot;text-autospace:none&quot;&gt;&lt;span style=&quot;font-family:Calibri,sans-serif&quot;&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;Censored sample arises in a life-testing experiment whenever the experimenter does not observe the failure times of all units placed on a life-test&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;In medical or industrial studies&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;, &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;researchers have to treat the censored data because they usually do not have sufficient time to observe the lifetime of all subjects in the study&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;There are different types of censoring&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;The most common censoring schemes are type I and type&amp;nbsp; II censoring schemes&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. Progressively type II censoring is also one of the most important methods of censoring. &lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:11pt&quot;&gt;&lt;span style=&quot;line-height:17.0pt&quot;&gt;&lt;span style=&quot;text-autospace:none&quot;&gt;&lt;span style=&quot;font-family:Calibri,sans-serif&quot;&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;One of the most common questions any statistician gets asked is &amp;quot;How large a sample size do I need?&amp;quot;&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;Researchers are often surprised to find out that the answer depends on a number of&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm; &lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;factors and they have to give the statistician some information before they can get an answer&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;So far different answers have been given to respond this question by considering different criteria&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span dir=&quot;RTL&quot; lang=&quot;FA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;font-family:&quot;Arial&quot;,sans-serif&quot;&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:11pt&quot;&gt;&lt;span style=&quot;line-height:17.0pt&quot;&gt;&lt;span style=&quot;text-autospace:none&quot;&gt;&lt;span style=&quot;font-family:Calibri,sans-serif&quot;&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;Cost criterion is one of the criteria that has always been of interest to researchers&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;So far&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;, &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;many researchers have used this criterion for determining the size of samples in different censoring methods&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:11pt&quot;&gt;&lt;span style=&quot;line-height:17.0pt&quot;&gt;&lt;span style=&quot;text-autospace:none&quot;&gt;&lt;span style=&quot;font-family:Calibri,sans-serif&quot;&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;In some applications&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;, &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;such as clinical trials and quality control&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;, &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;it is almost impossible to have a fixed sample size all the time because some observations may be missing for various reasons&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;In other words&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;, &lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;the sample size is a random variable&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;. &lt;/span&gt;&lt;span dir=&quot;RTL&quot; lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;font-family:&quot;Arial&quot;,sans-serif&quot;&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:11pt&quot;&gt;&lt;span style=&quot;line-height:17.0pt&quot;&gt;&lt;span style=&quot;text-autospace:none&quot;&gt;&lt;span style=&quot;font-family:Calibri,sans-serif&quot;&gt;&amp;nbsp;&lt;b&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;Material and methods&lt;/span&gt;&lt;/b&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:11pt&quot;&gt;&lt;span style=&quot;line-height:17.0pt&quot;&gt;&lt;span style=&quot;text-autospace:none&quot;&gt;&lt;span style=&quot;font-family:Calibri,sans-serif&quot;&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;In this paper, a cost function is introduced. Then, assuming that the sample size of progressively type II censoring is a random variable from the truncated binomial distribution, the optimal parameter of sample size distribution in progressively type II censoring, is determined. This optimal parameter is determined so that the introduced cost function does not exceed a pre-determined value, say &lt;span style=&quot;position:relative&quot;&gt;&lt;span style=&quot;top:3.0pt&quot;&gt;&lt;img alt=&quot;&quot; src=&quot;file:///C:UsersUser1AppDataLocalTempmsohtmlclip1�1clip_image002.gif&quot; style=&quot;width:17px; height:22px&quot; &gt;&lt;/span&gt;&lt;/span&gt;. In this article, the exponential distribution is considered for lifetimes of observations. A simulation study is also provided to evaluate the obtained results. Finally, the conclusion of the article is presented.&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:11pt&quot;&gt;&lt;span style=&quot;line-height:17.0pt&quot;&gt;&lt;span style=&quot;text-autospace:none&quot;&gt;&lt;span style=&quot;font-family:Calibri,sans-serif&quot;&gt;&lt;b&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;Results and discussion&lt;/span&gt;&lt;/b&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:12pt&quot;&gt;&lt;span style=&quot;line-height:17.0pt&quot;&gt;&lt;span new=&quot;&quot; roman=&quot;&quot; style=&quot;font-family:&quot; times=&quot;&quot;&gt;&lt;span lang=&quot;FA&quot; style=&quot;font-size:10.0pt&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;We have computed the values of the expected cost function by considering three different censoring schemes&amp;lrm;. &amp;lrm;The results show that the expected cost function is an increasing function of &lt;i&gt;m&lt;/i&gt; but a decreasing function of &amp;theta;, &amp;lrm;when other components are fixed&amp;lrm;, &amp;lrm;as we expected&amp;lrm;. &amp;nbsp;Also, we can find that considering type II censoring leads to better results than other censoring schemes&amp;lrm;. On the other hand, we can conclude that type II censoring provides the minimum cost among two other censoring schemes. In the sequel, by assuming an upper bound for the cost function, say &lt;span style=&quot;position:relative&quot;&gt;&lt;span style=&quot;top:3.0pt&quot;&gt;&lt;img alt=&quot;&quot; src=&quot;file:///C:UsersUser1AppDataLocalTempmsohtmlclip1�1clip_image002.gif&quot; style=&quot;width:17px; height:22px&quot; &gt;&lt;/span&gt;&lt;/span&gt;, the optimal parameter of sample size distribution is obtained.&amp;nbsp; &lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:11pt&quot;&gt;&lt;span style=&quot;line-height:17.0pt&quot;&gt;&lt;span style=&quot;font-family:Calibri,sans-serif&quot;&gt;&lt;b&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;Conclusion&lt;/span&gt;&lt;/b&gt;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;br&gt;
&lt;span style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span calibri=&quot;&quot; style=&quot;font-family:&quot;&gt;Determining the optimal sample size is one of the issues that has been studied by many researchers. In some cases, it is not possible for the sample size to be a fixed and pre-determined value. In other words, the sample size is a random variable. In this paper, assuming that the sample size of progressively type II censoring is a random variable from the truncated binomial distribution, the optimal parameter of the sample size distribution is determined. The criterion used in this research is the cost criterion. Next, the optimal parameter of the sample size distribution is determined so that the value of the cost function is less than the specified and predetermined value, say &lt;span style=&quot;position:relative&quot;&gt;&lt;span style=&quot;top:3.0pt&quot;&gt;&lt;img alt=&quot;&quot; src=&quot;file:///C:UsersUser1AppDataLocalTempmsohtmlclip1�1clip_image002.gif&quot; style=&quot;width:17px; height:22px&quot; &gt;&lt;/span&gt;&lt;/span&gt;. The results of the paper show that the type II censoring provides less values for the cost function. For all three censorsing schemes, the cost function is an increasing function of &lt;i&gt;m&lt;/i&gt; but a decreasing function of &amp;theta;, &lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span calibri=&quot;&quot; style=&quot;font-family:&quot;&gt;when other components are fixed&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span calibri=&quot;&quot; style=&quot;font-family:&quot;&gt;, &lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span calibri=&quot;&quot; style=&quot;font-family:&quot;&gt;as we expected&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span lang=&quot;AR-SA&quot; style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span arial=&quot;&quot; style=&quot;font-family:&quot;&gt;&amp;lrm;&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;&lt;span style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span calibri=&quot;&quot; style=&quot;font-family:&quot;&gt;.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt; &lt;span style=&quot;font-size:10.0pt&quot;&gt;&lt;span style=&quot;line-height:107%&quot;&gt;&lt;span calibri=&quot;&quot; style=&quot;font-family:&quot;&gt;As a result, the best case scenario is taking into account the type II censoring scheme, selecting smaller values for &lt;i&gt;m&lt;/i&gt;, larger values ​​for &amp;theta;, and smaller values for the parameter of sample size distribution.&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;</abstract>
	<keyword_fa>اندازه نمونه تصادفی, بهینه‌سازی, تابع هزینه</keyword_fa>
	<keyword>Random Sample Size, Optimaization, Cost Function</keyword>
	<start_page>49</start_page>
	<end_page>64</end_page>
	<web_url>http://mmr.khu.ac.ir/browse.php?a_code=A-10-1115-1&amp;slc_lang=fa&amp;sid=1</web_url>


<author_list>
	<author>
	<first_name>Elham</first_name>
	<middle_name></middle_name>
	<last_name>Basiri</last_name>
	<suffix></suffix>
	<first_name_fa>الهام</first_name_fa>
	<middle_name_fa></middle_name_fa>
	<last_name_fa>بصیری</last_name_fa>
	<suffix_fa></suffix_fa>
	<email>elham_basiri2000@yahoo.com</email>
	<code>10031947532846005461</code>
	<orcid>10031947532846005461</orcid>
	<coreauthor>Yes
</coreauthor>
	<affiliation>Kosar University of Bojnord</affiliation>
	<affiliation_fa>دانشگاه کوثر بجنورد</affiliation_fa>
	 </author>


</author_list>


	</article>
</articleset>
</journal>
