<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:prism="http://prismstandard.org/namespaces/basic/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns="http://purl.org/rss/1.0/" xmlns:admin="http://webns.net/mvcb/">
<channel rdf:about="https://thescipub.com/feed/jmss/issue-910.rss">
<title>Volume 12, Issue 2 (2016) | Journal of Mathematics and Statistics</title>
<description>Volume 12, Issue 2 (2016) | Journal of Mathematics and Statistics</description>
<link>https://thescipub.com/jmss/issue/910</link>
<admin:generatorAgent rdf:resource="https://thescipub.com/"/>
<admin:errorReportsTo rdf:resource="mailto:support@thescipub.com"/>
<dc:publisher>Science Publications</dc:publisher>
<dc:language>en</dc:language>
<prism:publicationName>Science Publications</prism:publicationName>
<items>
<rdf:Seq>
<rdf:li rdf:resource="https://thescipub.com/jmss/jmssp.2016.65.76"/><rdf:li rdf:resource="https://thescipub.com/jmss/jmssp.2016.77.85"/><rdf:li rdf:resource="https://thescipub.com/jmss/jmssp.2016.86.98"/><rdf:li rdf:resource="https://thescipub.com/jmss/jmssp.2016.99.106"/><rdf:li rdf:resource="https://thescipub.com/jmss/jmssp.2016.107.114"/><rdf:li rdf:resource="https://thescipub.com/jmss/jmssp.2016.115.118"/><rdf:li rdf:resource="https://thescipub.com/jmss/jmssp.2016.119.126"/><rdf:li rdf:resource="https://thescipub.com/jmss/jmssp.2016.127.134"/></rdf:Seq>
</items>
</channel><item rdf:about="https://thescipub.com/jmss/jmssp.2016.65.76">
    <title><![CDATA[Some Contributions to the Theory of Abstract Degenerate Volterra Integro-Differential Equations]]></title>
    <link>https://thescipub.com/jmss/jmssp.2016.65.76</link>
    <content:encoded>
        <![CDATA[<p>Journal of Mathematics and Statistics, Published online: 17 June 2016; <a href="https://thescipub.com/jmss/jmssp.2016.65.76">doi:10.3844/jmssp.2016.65.76</a></p>In this study, we contribute to the existing theory of abstract degenerate Volterra integro-differential equations in sequentially complete locally convex spaces. We investigate a class of abstract de...]]></content:encoded>
    <dc:title><![CDATA[Some Contributions to the Theory of Abstract Degenerate Volterra Integro-Differential Equations]]></dc:title><dc:creator>Marko  Kostić</dc:creator><dc:identifier>doi:10.3844/jmssp.2016.65.76</dc:identifier>
    <dc:source>Journal of Mathematics and Statistics, Published online: 2016-06-17; | doi:10.3844/jmssp.2016.65.76</dc:source>
    <dc:date>2016-06-17</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jmssp.2016.65.76</prism:doi>
    <prism:url>https://thescipub.com/jmss/jmssp.2016.65.76</prism:url>
    </item><item rdf:about="https://thescipub.com/jmss/jmssp.2016.77.85">
    <title><![CDATA[Burr-X Model Estimate using Bayesian and non-Bayesian Approaches]]></title>
    <link>https://thescipub.com/jmss/jmssp.2016.77.85</link>
    <content:encoded>
        <![CDATA[<p>Journal of Mathematics and Statistics, Published online: 6 May 2016; <a href="https://thescipub.com/jmss/jmssp.2016.77.85">doi:10.3844/jmssp.2016.77.85</a></p>The present paper is aimed at developing Bayesian and Maximum Likelihood estimations (ML) of the Burr type-X model of distribution when data are gathered from Type-II cumulative censoring with binomia...]]></content:encoded>
    <dc:title><![CDATA[Burr-X Model Estimate using Bayesian and non-Bayesian Approaches]]></dc:title><dc:creator>Abdullah Y. Al-Hossain</dc:creator><dc:identifier>doi:10.3844/jmssp.2016.77.85</dc:identifier>
    <dc:source>Journal of Mathematics and Statistics, Published online: 2016-05-06; | doi:10.3844/jmssp.2016.77.85</dc:source>
    <dc:date>2016-05-06</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jmssp.2016.77.85</prism:doi>
    <prism:url>https://thescipub.com/jmss/jmssp.2016.77.85</prism:url>
    </item><item rdf:about="https://thescipub.com/jmss/jmssp.2016.86.98">
    <title><![CDATA[Proportional Hazard Inverse Weibull Distribution and Associated Inference]]></title>
    <link>https://thescipub.com/jmss/jmssp.2016.86.98</link>
    <content:encoded>
        <![CDATA[<p>Journal of Mathematics and Statistics, Published online: 18 April 2016; <a href="https://thescipub.com/jmss/jmssp.2016.86.98">doi:10.3844/jmssp.2016.86.98</a></p>In this study, we have considered the proportional hazard version of the inverse Weibull distribution. It has been shown that the density and hazard rate functions are unimodal and the mean residual l...]]></content:encoded>
    <dc:title><![CDATA[Proportional Hazard Inverse Weibull Distribution and Associated Inference]]></dc:title><dc:creator>Suja M. Aboukhamseen</dc:creator><dc:creator>Mohamed E. Ghitany</dc:creator><dc:creator>Ramesh C. Gupta</dc:creator><dc:identifier>doi:10.3844/jmssp.2016.86.98</dc:identifier>
    <dc:source>Journal of Mathematics and Statistics, Published online: 2016-04-18; | doi:10.3844/jmssp.2016.86.98</dc:source>
    <dc:date>2016-04-18</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jmssp.2016.86.98</prism:doi>
    <prism:url>https://thescipub.com/jmss/jmssp.2016.86.98</prism:url>
    </item><item rdf:about="https://thescipub.com/jmss/jmssp.2016.99.106">
    <title><![CDATA[Testing VaR Accuracy for CDS Portfolios Using Historical Simulation and Delta-Normal Models]]></title>
    <link>https://thescipub.com/jmss/jmssp.2016.99.106</link>
    <content:encoded>
        <![CDATA[<p>Journal of Mathematics and Statistics, Published online: 16 April 2016; <a href="https://thescipub.com/jmss/jmssp.2016.99.106">doi:10.3844/jmssp.2016.99.106</a></p>This paper studies the accuracy of the VaR using the Delta-Normal and Historical approaches in measuring the risk of CDS portfolios in three different zones, US, Europe and Asia, for the period March ...]]></content:encoded>
    <dc:title><![CDATA[Testing VaR Accuracy for CDS Portfolios Using Historical Simulation and Delta-Normal Models]]></dc:title><dc:creator>Viviane Y. Naimy</dc:creator><dc:identifier>doi:10.3844/jmssp.2016.99.106</dc:identifier>
    <dc:source>Journal of Mathematics and Statistics, Published online: 2016-04-16; | doi:10.3844/jmssp.2016.99.106</dc:source>
    <dc:date>2016-04-16</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jmssp.2016.99.106</prism:doi>
    <prism:url>https://thescipub.com/jmss/jmssp.2016.99.106</prism:url>
    </item><item rdf:about="https://thescipub.com/jmss/jmssp.2016.107.114">
    <title><![CDATA[Randomized Response Procedure for the Estimation of the Population Ratio using Ranked Set Sampling]]></title>
    <link>https://thescipub.com/jmss/jmssp.2016.107.114</link>
    <content:encoded>
        <![CDATA[<p>Journal of Mathematics and Statistics, Published online: 27 April 2016; <a href="https://thescipub.com/jmss/jmssp.2016.107.114">doi:10.3844/jmssp.2016.107.114</a></p>In this study we deal with the estimation of the population ratio, when a Randomized Response (RR) procedure is used for collecting responses and Ranked Set Sampling (RSS) is the selection method. The...]]></content:encoded>
    <dc:title><![CDATA[Randomized Response Procedure for the Estimation of the Population Ratio using Ranked Set Sampling]]></dc:title><dc:creator>Agustin  Santiago</dc:creator><dc:creator>Carlos N. Bouza</dc:creator><dc:creator>J. Maclovio Sautto</dc:creator><dc:creator>Amer Ibrahim Al-Omari</dc:creator><dc:identifier>doi:10.3844/jmssp.2016.107.114</dc:identifier>
    <dc:source>Journal of Mathematics and Statistics, Published online: 2016-04-27; | doi:10.3844/jmssp.2016.107.114</dc:source>
    <dc:date>2016-04-27</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jmssp.2016.107.114</prism:doi>
    <prism:url>https://thescipub.com/jmss/jmssp.2016.107.114</prism:url>
    </item><item rdf:about="https://thescipub.com/jmss/jmssp.2016.115.118">
    <title><![CDATA[Hilbert-Type Inequalities Revisited]]></title>
    <link>https://thescipub.com/jmss/jmssp.2016.115.118</link>
    <content:encoded>
        <![CDATA[<p>Journal of Mathematics and Statistics, Published online: 28 April 2016; <a href="https://thescipub.com/jmss/jmssp.2016.115.118">doi:10.3844/jmssp.2016.115.118</a></p>Considering different parameters, Hilbert-type integral inequality for functions f(x), g(x) in L2[0, ∞) will be generalized.]]></content:encoded>
    <dc:title><![CDATA[Hilbert-Type Inequalities Revisited]]></dc:title><dc:creator>Waleed  Abuelela</dc:creator><dc:identifier>doi:10.3844/jmssp.2016.115.118</dc:identifier>
    <dc:source>Journal of Mathematics and Statistics, Published online: 2016-04-28; | doi:10.3844/jmssp.2016.115.118</dc:source>
    <dc:date>2016-04-28</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jmssp.2016.115.118</prism:doi>
    <prism:url>https://thescipub.com/jmss/jmssp.2016.115.118</prism:url>
    </item><item rdf:about="https://thescipub.com/jmss/jmssp.2016.119.126">
    <title><![CDATA[Estimation for Unknown Parameters of the Burr Type-XII Distribution Based on an Adaptive Progressive Type-II Censoring Scheme]]></title>
    <link>https://thescipub.com/jmss/jmssp.2016.119.126</link>
    <content:encoded>
        <![CDATA[<p>Journal of Mathematics and Statistics, Published online: 29 April 2016; <a href="https://thescipub.com/jmss/jmssp.2016.119.126">doi:10.3844/jmssp.2016.119.126</a></p>In this study, the Maximum Likelihood Estimation (MLE) and Bayes estimation are exploited to make interval estimation based on adaptive progressive Type-II censoring for the Burr Type-XII distribution...]]></content:encoded>
    <dc:title><![CDATA[Estimation for Unknown Parameters of the Burr Type-XII Distribution Based on an Adaptive Progressive Type-II Censoring Scheme]]></dc:title><dc:creator>Montaser M. Amein</dc:creator><dc:identifier>doi:10.3844/jmssp.2016.119.126</dc:identifier>
    <dc:source>Journal of Mathematics and Statistics, Published online: 2016-04-29; | doi:10.3844/jmssp.2016.119.126</dc:source>
    <dc:date>2016-04-29</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jmssp.2016.119.126</prism:doi>
    <prism:url>https://thescipub.com/jmss/jmssp.2016.119.126</prism:url>
    </item><item rdf:about="https://thescipub.com/jmss/jmssp.2016.127.134">
    <title><![CDATA[Numerical Solution of First Order Initial Value Problems Using a Self-Starting Implicit Two-Step Obrechkoff-Type Block Method]]></title>
    <link>https://thescipub.com/jmss/jmssp.2016.127.134</link>
    <content:encoded>
        <![CDATA[<p>Journal of Mathematics and Statistics, Published online: 13 June 2016; <a href="https://thescipub.com/jmss/jmssp.2016.127.134">doi:10.3844/jmssp.2016.127.134</a></p>The conventional two-step implicit Obrechkoff method is a discrete scheme that requires additional starting values when implemented for the numerical solution of first order initial value problems. Th...]]></content:encoded>
    <dc:title><![CDATA[Numerical Solution of First Order Initial Value Problems Using a Self-Starting Implicit Two-Step Obrechkoff-Type Block Method]]></dc:title><dc:creator>Zurni  Omar</dc:creator><dc:creator>Oluwaseun  Adeyeye</dc:creator><dc:identifier>doi:10.3844/jmssp.2016.127.134</dc:identifier>
    <dc:source>Journal of Mathematics and Statistics, Published online: 2016-06-13; | doi:10.3844/jmssp.2016.127.134</dc:source>
    <dc:date>2016-06-13</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jmssp.2016.127.134</prism:doi>
    <prism:url>https://thescipub.com/jmss/jmssp.2016.127.134</prism:url>
    </item></rdf:RDF>