International Journal of Statistics and Probability
http://ccsenet.org/journal/index.php/ijsp
<em><strong>International Journal of Statistics and Probability</strong> </em>(ISSN: 1927-7032; E-ISSN: 1927-7040) is an open-access, international, double-blind peer-reviewed journal published by the Canadian Center of Science and Education. This journal, published <strong>quarterly</strong> (February, May, August and November) in both<strong> print and online versions</strong>, keeps readers up-to-date with the latest developments in all areas of statistics and probability.<img src="/journal/public/site/images/ijsp/ijsp.jpg" alt="ijsp" hspace="20" vspace="20" width="201" height="264" align="right" /><p><strong>The scopes of the journal </strong>include, but are not limited to, the following topics: computational statistics, design of experiments, sample survey, statistical modelling, statistical theory, probability theory.</p><p>This journal accepts article submissions<strong> <a href="/journal/index.php/ijsp/information/authors">online</a> or by <a href="mailto:ijsp@ccsenet.org">e-mail</a> </strong>(ijsp@ccsenet.org).</p><p><strong><strong>ABSTRACTING AND INDEXING:</strong></strong></p><ul><li><strong>DOAJ</strong></li><li><strong>EBSCOhost</strong></li><li>Google Scholar</li><li>JournalTOCs</li><li>Library and Archives Canada</li><li>LOCKSS</li><li>PKP Open Archives Harvester</li><li><strong>ProQuest</strong></li><li>SHERPA/RoMEO</li><li>Standard Periodical Directory</li></ul>en-US<p>Submission of an article implies that the work described has not been published previously (except in the form of an abstract or as part of a published lecture or academic thesis), that it is not under consideration for publication elsewhere, that its publication is approved by all authors and tacitly or explicitly by the responsible authorities where the work was carried out, and that, if accepted, will not be published elsewhere in the same form, in English or in any other language, without the written consent of the Publisher. The Editors reserve the right to edit or otherwise alter all contributions, but authors will receive proofs for approval before publication.</p><p><br />Copyrights for articles published in CCSE journals are retained by the authors, with first publication rights granted to the journal. The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.</p>ijsp@ccsenet.org (Wendy Smith)ijsp@ccsenet.org (Technical Support)Thu, 18 Dec 2014 00:00:00 -0800OJS 2.3.8.0http://blogs.law.harvard.edu/tech/rss60Polynomially Adjusted Saddlepoint Density Approximations
http://ccsenet.org/journal/index.php/ijsp/article/view/41014
Improved density approximations are obtained by applying certain moment based polynomial adjustments to the saddlepoint approximation. The proposed technique relies on the saddlepoint approximation to the distribution function of a continuous random variable as well. Additionally, a hybrid density estimate is being introduced. Rational functions are also utilized as adjustments. Several numerical examples reveal that, overall, the methodologies that are advocated in this paper consistently produce more accurate distributional approximations.Serge B. Provost, Susan Z. Shenghttp://ccsenet.org/journal/index.php/ijsp/article/view/41014Thu, 18 Dec 2014 18:08:54 -0800Evaluation of Academic Level of Sci-tech Journals Based on Rough Set and TOPSIS
http://ccsenet.org/journal/index.php/ijsp/article/view/40684
<p>This paper aims to objectively evaluate the academic level of sci-tech journals, reducing mistakes and random errors caused by human factors in traditional academic evaluation. Evaluation indicators of sci-tech journals are reduced based on equivalence relation thought in Rough set theory, removing the miscellaneous indicators, and form the core evaluation indicator system. By studying the degree of importance of the core evaluation indicators’ attributes to determine the appropriate weight, to avoid interference of human factors in the weight determination, so that the evaluation results of sci-tech journals can be more objective. Combine obtained weight of core evaluation indicators with related data, and using TOPSIS method to make comprehensive evaluation rankings for journals. Finally, using the model to validate data of sci-tech journals, and achieved good results, proved the feasibility and effectiveness of the model.</p>Nie He, Yuan-Biao Zhang, Zhen Zhang, Xin-Guang Lvhttp://ccsenet.org/journal/index.php/ijsp/article/view/40684Thu, 18 Dec 2014 18:14:00 -0800Exact Simulation for Fork-Join Networks with Heterogeneous Service
http://ccsenet.org/journal/index.php/ijsp/article/view/41295
This paper considers a fork-join network with a group of heterogeneous servers in each service station, e.g. servers having different service rate. The main research interests are the properties of such fork-join networks in equilibrium, such as distributions of response times, maximum queue lengths and load carried by servers. This paper uses exact Monte-Carlo simulation methods to estimate the characteristics of<br />heterogeneous fork-join networks in equilibrium, for which no explicit formulas are available. The algorithm developed is based on coupling from the past. The efficiency of the sampling algorithm is shown theoretically and via simulation.Hongsheng Daihttp://ccsenet.org/journal/index.php/ijsp/article/view/41295Thu, 18 Dec 2014 18:19:45 -0800Dose Finding Method in Joint Modeling of Efficacy and Safety Endpoints in Phase II Studies
http://ccsenet.org/journal/index.php/ijsp/article/view/41443
<p>Determination of appropriate dose(s) to advance into Phase III trials is one of the most challenging and important tasks during drug development. Selecting a dose too high may result in unacceptable safety problems, while a too low dose may lead to ineffective drugs. Proper estimation of dose-response profiles for relevant safety and efficacy endpoints allows the reliable evaluation of the risk-benefit profile of a drug at the end of Phase II, as well as the selection of appropriate doses to be brought into confirmatory Phase III trials. Thus how to select dose(s) in Phase II trials by combining information about the efficacy and safety in a joint model setting may play a key role in drug development programs and can serve as a gate-keeper for large confirmatory Phase III trials with greater chance of success.</p> <p>Dose finding methods through joint modeling of both efficacy and safety endpoints are studied in this paper. To be more specific, we extend the popular MCP-Mod dose finding method (Bretz et al., 2005), which considered only the efficacy endpoint, to the method that incorporates both efficacy and safety endpoints through joint modeling. Method of parameter estimation for the extended models, and methods of selection of dose(s) to be brought into confirmatory Phase III trials based on Phase II study data are discussed in the paper. The performances of the proposed methods are evaluated through simulations.</p>Aiyang Tao, Yong Lin, Jose Pinheiro, Weichung Joe Shihhttp://ccsenet.org/journal/index.php/ijsp/article/view/41443Thu, 18 Dec 2014 18:25:18 -0800Flexible Bivariate Binary Models for Estimating the Efficacy of Phototherapy for Newborns with Jaundice
http://ccsenet.org/journal/index.php/ijsp/article/view/41892
In this work we analyse the efficacy of phototherapy (treatment) on the probability of being hyperbilirubinemic (outcome) in infants. A realistic quantification of the relationship between treatment and outcome can be challenging for various reasons. First, the probability of interest might be too small. Second, confounding unmeasured variables may exist which can bias the efficacy of phototherapy at preventing significant hyperbilirubinemia. Third, relationships between covariates and the outcome variable may exhibit non-linear patterns that, if not accounted for, can bias the relationship of interest. One way of dealing with the second and third issues is to use a semiparametric recursive bivariate probit model. To address the first issue as well, we explore an extension of this model which accounts for the fact that being hyperbilirubinemic can be regarded as a rare event. The proposed approach combines the marginal distributions of treatment and outcome using copulae, and uses asymmetric link functions to deal with rare outcome events. The main features underpinning the use of asymmetric link functions within semiparametric bivariate binary models are discussed.Giampiero Marra, Rosalba Radicehttp://ccsenet.org/journal/index.php/ijsp/article/view/41892Thu, 18 Dec 2014 18:30:27 -0800Characterization of the Skew-Normal Distribution Via Order Statistics and Record Values
http://ccsenet.org/journal/index.php/ijsp/article/view/42102
Characterization of a probability distribution is the investigation of those unique properties enjoyed by that distribution. In this article the general condition moments technique is used to obtain some new characterization results for the skew-normal distribution based on the order statistics as well as the record values of a random sample drawn from this distribution. The achieved results can be used to improve fitting and modeling skew data using the skew-normal distribution. Further, the new results are specialized to the standard normal distribution.M. Gharib, M.M. Mohie El-Din, A. Sharawyhttp://ccsenet.org/journal/index.php/ijsp/article/view/42102Sun, 21 Dec 2014 19:43:01 -0800The Explicit Solution and Precise Distribution of CKLS Model under Girsanov Transform
http://ccsenet.org/journal/index.php/ijsp/article/view/42640
The relation between CKLS model and CIR model will be investigatedin this paper. It will be shown that under a suitabletransformation, any CKLS model of order $\frac{1}{2}<\gamma<1$ or$\gamma> 1$ corresponds to a CIR model under a new probabilityspace. Moreover, the explicit solution and the precise distributionof the CKLS model at any time $t$ are obtained under the newprobability measure. The moment estimation of CKLS model will be given finally.Yunjiao Hu, Guangqiang Lan, Chong Zhanghttp://ccsenet.org/journal/index.php/ijsp/article/view/42640Wed, 07 Jan 2015 17:41:04 -0800Large Deviation Principle for the Empirical Degree Measure of Preferential Attachment Random Graphs
http://ccsenet.org/journal/index.php/ijsp/article/view/35771
We consider preferential attachment random graphs which may be obtained as follows: It starts with a single node. If a new node appears, it is linked by an edge to one or more existing node(s) with a probability proportional to function of their degree. For a class of linear preferential attachment random graphs we find a large deviation principle (LDP) for<br />the empirical degree measure. In the course of the prove this LDP we establish an LDP for the empirical degree and pair distribution see Theorem 2.3, of the fitness preferential attachment model of random graphs.K. Doku-Amponsah, F. O. Mettle, E. N. N. Norteyhttp://ccsenet.org/journal/index.php/ijsp/article/view/35771Wed, 07 Jan 2015 17:51:38 -0800Independence Distribution-preserving Covariance Structures for the Likelihood Ratio Test for LXB=0 in the General Linear Model
http://ccsenet.org/journal/index.php/ijsp/article/view/41049
We derive an explicit representation of the general non-i.i.d. error covariance matrix of the general linear model vector such that the likelihood ratio test statistic for testing certain linear restrictions on the parameter vector is robust against certain forms of dependency and heteroscedasticity. In doing so, we correct two proposed explicit covariance matrix characterizations given in Khatri (1981).Phil Dean Younghttp://ccsenet.org/journal/index.php/ijsp/article/view/41049Fri, 09 Jan 2015 19:15:22 -0800Large Deviation Result for the Empirical Locality Measure of Typed Random Geometric Graphs
http://ccsenet.org/journal/index.php/ijsp/article/view/41819
In this article for a finite typed random geometric graph we define the empirical locality distribution, which records the number of nodes of a given type linked to a given number of nodes of each type. We find large<br />deviation principle (LDP) for the \emph{ empirical locality measure}<br />given the empirical pair measure and the empirical type measure of<br />the typed random geometric graphs. From this LDP, we derive large<br />deviation principles for the \emph{degree measure and the proportion of detached nodes} in the classical Erd\H{o}s-R\'{e}nyi graph defined on $[0, 1]^d.$ This graphs have been suggested by (Canning and Penman, 2003) as a possible extension to the randomly typed random graphs.Kwabena Doku-Amponsahhttp://ccsenet.org/journal/index.php/ijsp/article/view/41819Sun, 11 Jan 2015 17:36:26 -0800College Basketball Coach Evaluation Based on Dynamic DHGF Evaluation Model
http://ccsenet.org/journal/index.php/ijsp/article/view/44196
<p class="2">The use of mathematical evaluation model is more and more widely, including the comprehensive evaluation of college coaches. In this paper, we build DHGF model using the Delphi method, AHP, Gray Relation and Fuzzy Judgment to evaluate college couches quantitatively. Based on DHGF model, we analyze the influence of timeline on the scores of evaluation indexes, get Plus Function, so as to adjust experts score. So we get dynamic DHGF evaluation model. Then, we apply the model to men's college basketball matches. After that, we discuss that this model is applicable for choosing the best college coach or coaches (past or present) from among either male or female coaches in all sports fields. And we will apply the model to evaluation problems with large time span or with many affecting factors.</p>Si-Jing Meng, Yuan-Biao Zhang, Gui-Sen Xu, Jun-Ta Wuhttp://ccsenet.org/journal/index.php/ijsp/article/view/44196Mon, 12 Jan 2015 00:00:00 -0800The Burr XII Negative Binomial Distribution with Applications to Lifetime Data
http://ccsenet.org/journal/index.php/ijsp/article/view/44352
A five-parameter model, called the Burr XII negative binomial distribution, is defined and studied. The new model contains as special cases some important lifetime distributions discussed in the literature, such as the log-logistic, Weibull, Pareto type II and Burr XII distributions, among several others. We derive the ordinary and incomplete moments, generating and quantile functions, mean deviations, reliability and two types of entropy. The order statistics and their moments are investigated. The method of maximum likelihood is proposed for estimating the model parameters. We obtain the observed information matrix. An application to real data demonstrates that the new distribution can provide a better fit than other classical lifetime models.Manoel Wallace A. Ramos, Ana Percontini, Gauss M. Cordeiro, Ronaldo V. da Silvahttp://ccsenet.org/journal/index.php/ijsp/article/view/44352Sat, 17 Jan 2015 00:00:00 -0800Visualizing and Testing the Multivariate Linear Regression Model
http://ccsenet.org/journal/index.php/ijsp/article/view/43460
Recent results make the multivariate linear regression model much easier to use. This model has $m \geq 2$ response variables. Results by Kakizawa (2009) and Su and Cook (2012) can be used to explain the large sample theory of the least squares estimator and of the widely used Wilks' $\Lambda$, Pillai's trace, and Hotelling Lawley trace test statistics. Kakizawa (2009) shows that these statistics have the same limiting distribution. This paper reviews these results and gives two theorems to show that the Hotelling Lawley test generalizes the usual partial $F$ test for $m = 1$ response variable to $m \geq 1$ response variables. Plots for visualizing the model are also given, and can be used to check goodness and lack of fit, to check for outliers and influential cases, and to check whether the error distribution is multivariate normal or from some other elliptically contoured distribution.David J. Olive, Lasanthi C. R. Pelawa Watagoda, Hasthika S. Rupasinghe Arachchige Donhttp://ccsenet.org/journal/index.php/ijsp/article/view/43460Wed, 21 Jan 2015 16:36:29 -0800Reweighted Nadaraya-Watson Estimator of the Regression Mean
http://ccsenet.org/journal/index.php/ijsp/article/view/39379
<p>In this paper, the estimation of the regression mean using the Reweighted Nadaraya-Watson (RNW) estimator has been considered. The RNW is a modification of the Nadaraya-Watson (NW) estimator in order to obtain some more refinement estimator. We have considered some conditions under which the asymptotic normality of the proposed estimator has been derived. Then we generalized this result to the multivariate case by considering the estimation of the regression mean at distinct points.</p>Raid B. Salha, Hazem I. El Shekh Ahmedhttp://ccsenet.org/journal/index.php/ijsp/article/view/39379Sun, 25 Jan 2015 17:35:50 -0800Estimating Explained Variation of a Latent Scale Dependent Variable Underlying a Binary Indicator of Event Occurrence
http://ccsenet.org/journal/index.php/ijsp/article/view/39718
The coecient of determinant, also known as the R2 statistic, is widely used as a measure of theproportion of explained variation in the context of a linear regression model. In many real lifeevents, interests may lie on measuring the proportion of explained variation, rho^2, of a latent scaledependent variable U which follows a multiple regression model. But in practice, U may not beobservable and is represented by its binary proxy. In such situations, use of logistic regressionanalysis is a popular choice. Many analogues to R2 type statistics have been proposed to measureexplained variation in the context of logistic regression. McFadden's R2 measure stands out fromothers because of its intuitive interpretation and its independence on the proportion of successin the sample. It, however, severely underestimates the proportion of explained variation of theunderlying linear model. In this research we present a method for estimating the explained variationfor the underlying linear model using the McFadden's R2 statistics. When used in a real lifedataset, our method estimated rho^2 of the underlying model within an acceptable margin of error.Dinesh Sharma, Amanda Miller, Caroline Hollingsworthhttp://ccsenet.org/journal/index.php/ijsp/article/view/39718Sun, 25 Jan 2015 17:38:12 -0800A Robust Approach to Identifying Differential Circulating miRNAs in Breast Cancer
http://ccsenet.org/journal/index.php/ijsp/article/view/44670
This article proposes and explores a robust approach to identifying differential circulating miRNAs in the plasma of patients with breast cancer. The proposed approach, developed in the framework of the M-estimation, is used to provide protection against potential outliers in miRNA expression data. As the study involves multiple comparisons<br />with a large number of circulating miRNAs, robust multiple tests are adopted at a given level of false discovery rate (FDR). Also, due to the uncertainties in the underlying distributions of the miRNA expression data sets, the p-values of the multiple tests are approximated using a permutation method. The empirical properties of the proposed robust tests are studied in simulations. An application is provided using miRNA expression data from a breast cancer study.Sanjoy K. Sinha, Abdus Sattarhttp://ccsenet.org/journal/index.php/ijsp/article/view/44670Tue, 27 Jan 2015 00:00:00 -0800Random Fuzzy Decision Models for Pharmaceutical R&D Project Investment under Uncertainty
http://ccsenet.org/journal/index.php/ijsp/article/view/43984
This paper considers an optimal stopping decision problem for pharmaceutical R&D project investment withoutrivalry in random fuzzy environments. Specifically, the R&D process can be regarded as a jump diffusion processof scientific knowledge full of complexity. Every jump represents a scientific breakthrough or a new knowledgediscovery. In classical R&D literature, the inter-arrival times between jumps are generally assumed as randomvariables which are exponentially distributed. Here, the inter-arrival times are treated as random fuzzy variablesobserve arbitrary distributions. Furthermore, the termination time of the project is incorporated into the R&Dmodels as a decision variable by allowing the decision-maker to sell the obtained technology at any point oftime. Three types of project return performance (expected net return, -optimistic net return and return reliability)are proposed and a spectrum of random fuzzy programming models are established to model the different R&Dinvestment decision problems according to the decision-maker’s attitude. Considering the complexity of thesemodels, the random fuzzy simulation is designed to estimate the values of project return performance and thesimultaneous perturbation stochastic approximation (SPSA) algorithm is employed to solve the proposed models.Finally, the effectiveness of the hybrid algorithm and the applicability of these models are illustrated by somenumerical examples.Changsheng Yi, Qiumei Jinhttp://ccsenet.org/journal/index.php/ijsp/article/view/43984Wed, 28 Jan 2015 17:39:57 -0800Reviewer Acknowledgements for International Journal of Statistics and Probability, Vol. 4, No. 1
http://ccsenet.org/journal/index.php/ijsp/article/view/44767
<p><em>International Journal of Statistics and Probability</em> wishes to acknowledge the following individuals for their assistance with peer review of manuscripts for this issue. Their help and contributions in maintaining the quality of the journal is greatly appreciated.</p> <p>Many authors, regardless of whether <em>International Journal of Statistics and Probability</em> publishes their work, appreciate the helpful feedback provided by the reviewers.</p> <p><strong>Reviewers for Volume 4, Number 1</strong></p> <p>Abd Allah Mohamed Abd Elfattah</p> <p>Anwar H Joarder</p> <p>Carolyn Huston</p> <p>Chin-Shang Li</p> <p>Encarnación Alvarez-Verdejo</p> <p>Farida Kachapova</p> <p>Gabriel A. Okyere</p> <p>Gane Samb Lo</p> <p>Hongsheng Dai</p> <p>Jacek Bia?ek</p> <p>Marcelo Bourguignon</p> <p>Michele Leonardo Bianchi</p> <p>Mirko D'Ovidio</p> <p>Philip Westgate</p> <p>Sajid Ali</p> <p>Sohair F. Higazi</p> <p>Tewfik Kernane</p> <p>Vyacheslav Abramov</p> <p>Wojciech Gamrot</p> <p>Zaixing Li</p> <p> </p> <p>Wendy Smith</p> <p>On behalf of,</p> <p>The Editorial Board of <em>International Journal of Statistics and Probability</em></p> <p>Canadian Center of Science and Education</p>Wendy Smithhttp://ccsenet.org/journal/index.php/ijsp/article/view/44767Thu, 29 Jan 2015 00:00:00 -0800