http://www.ccsenet.org/journal/index.php/ijsp/issue/feedInternational Journal of Statistics and Probability2017-10-19T20:37:32-07:00Wendy Smithijsp@ccsenet.orgOpen Journal Systems<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 <a href="http://web.ccsenet.org/">Canadian Center of Science and Education</a>. This journal, published <strong>bimonthly</strong> (<span>January, March, May, July, September and November</span>) 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" width="201" height="264" align="right" hspace="20" vspace="20" /><p><strong>The scopes of the journal </strong>include, but are not limited to, the following topics:</p><p><span lang="EN-US">Applied Probability and Statistics, Computational Statistics, Design of Experiments, Sample Survey, Statistical Modelling, Statistical Mechanics, Statistical Theory, Probability Theory. Statistical Education.</span></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><a href="http://media2.proquest.com/documents/titlelist_aerospace.xls"><strong><span lang="EN-US">Aerospace Database</span></strong></a></li><li><strong>BASE (Bielefeld Academic Search Engine)</strong></li><li><strong><a href="http://ezb.uni-regensburg.de/detail.phtml?bibid=AAAAA&colors=7&lang=en&jour_id=186278"><strong><span lang="EN-US">EZB</span> (<span lang="EN-US">Elektronische Zeitschriftenbibliothek</span>)</strong></a><br /></strong></li><li><strong>Google Scholar</strong></li><li><strong>JournalTOCs</strong></li><li><strong>Library and Archives Canada</strong></li><li><strong>LOCKSS</strong></li><li><strong>MIAR</strong></li><li><strong>PKP Open Archives Harvester</strong></li><li><strong>SHERPA/RoMEO</strong></li><li><strong>Standard Periodical Directory</strong></li><li><strong><a href="http://ulrichsweb.serialssolutions.com/login">Ulrich's</a></strong></li></ul>http://www.ccsenet.org/journal/index.php/ijsp/article/view/69742A Bayes Inference for Step-Stress Accelerated Life Testing2017-10-13T02:48:56-07:00Naijun Shansha@utep.eduHao Yang Tenghteng5@wisc.eduIn this article, we present a Bayesian analysis with convex tent priors for step-stress accelerated life testing (SSALT) using a proportional hazard (PH) model. As flexible as the cumulative exposure (CE) model in fitting step-stress data and its attractive mathematical properties, the PH model makes Bayesian inference much more accessible than the CE model. Two sampling methods through Markov chain Monte Carlo algorithms are employed for posterior inference of parameters. The performance of the methodology is investigated using both simulated and real data sets.<br /><br />2017-09-15T00:00:00-07:00Copyright (c) 2017 Naijun Sha, Hao Yang Tenghttp://www.ccsenet.org/journal/index.php/ijsp/article/view/69933Asymptotic Theory for Extended Asymmetric Multivariate GARCH Processes2017-10-13T02:48:56-07:00Manabu Asaim-asai@soka.ac.jpMichael McAleermichael.mcaleer@gmail.com<p>The paper considers various extended asymmetric multivariate conditional volatility models, and derives appropriate regularity conditions and associated asymptotic theory. This enables checking of internal consistency and allows valid statistical inferences to be drawn based on empirical estimation. For this purpose, we use an underlying vector random coefficient autoregressive process, for which we show the equivalent representation for the asymmetric multivariate conditional volatility model, to derive asymptotic theory for the quasi-maximum likelihood estimator. As an extension, we develop a new multivariate asymmetric long memory volatility model, and discuss the associated asymptotic properties.</p>2017-09-15T00:00:00-07:00Copyright (c) 2017 MANABU ASAI, Michael McAleerhttp://www.ccsenet.org/journal/index.php/ijsp/article/view/70608Use of Hotelling's T^2: Outlier Diagnostics in Mixtures2017-10-13T02:48:55-07:00D. R. Jensender@eservices.virginia.eduD. E. Ramirezder@eservices.virginia.eduGiven Gaussian observation vectors $[\seqcl{\BY}{n}]$ having a common mean and dispersion matrix, a pervading issue is to identify shifted observations of type $\{\BYi\!\to\!\BYi\!+\!\bdeli\}.$ Conventional usage enjoins Hotelling's $\Tisq$ diagnostics, derived and applied under the mutual independence of $[\seqcl{\BY}{n}]$. Independence often fails, yet the need to identify outliers nonetheless persists. Accordingly, the present study reexamines $\Tisq$ under dependencies to include equicorrelations and more general matrices. Such dependencies are found in the analysis of calibrated vector measurements and elsewhere. In addition, mixtures of these distributions having star--shaped contours arise on occasion in practice. Nonetheless, the $\Tisq$ diagnostics are shown to remain exact in level and power for all such mixtures. Moreover, further matrix distributions, not necessarily having finite moments, are seen to generalize $n$--dimensional spherical symmetry to include non--Gaussian matrices of order $(n\!\times\!k)$ supporting $\Tisq.$ For these the use of $\Tisq$ remains exact in level. These findings serve to expand considerably the range of applicability of $\Tisq$ in practice, to include matrix Cauchy and other heavy tailed distributions intrinsic to econometric and other studies. Case studies serve to illuminate the methodology.2017-09-15T00:00:00-07:00Copyright (c) 2017 D. R. Jensen, D. E. Ramirezhttp://www.ccsenet.org/journal/index.php/ijsp/article/view/70609Can Variances of Latent Variables be Scaled in Such a Way That They Correspond to Eigenvalues?2017-10-13T02:48:56-07:00Karl SchweizerK.Schweizer@psych.uni-frankfurt.deStefan TrocheK.Schweizer@psych.uni-frankfurt.deSiegbert ReißK.Schweizer@psych.uni-frankfurt.de<p class="1-Text">The paper reports an investigation of whether sums of squared factor loadings obtained in confirmatory factor analysis correspond to eigenvalues of exploratory factor analysis. The sum of squared factor loadings reflects the variance of the corresponding latent variable if the variance parameter of the confirmatory factor model is set equal to one. Hence, the computation of the sum implies a specific type of scaling of the variance. While the investigation of the theoretical foundations suggested the expected correspondence between sums of squared factor loadings and eigenvalues, the necessity of procedural specifications in the application, as for example the estimation method, revealed external influences on the outcome. A simulation study was conducted that demonstrated the possibility of exact correspondence if the same estimation method was applied. However, in the majority of realized specifications the estimates showed similar sizes but no correspondence. </p>2017-09-15T00:00:00-07:00Copyright (c) 2017 Karl Schweizer, Stefan Troche, Siegbert Reißhttp://www.ccsenet.org/journal/index.php/ijsp/article/view/69772Comments on a Two Queue Network2017-10-13T02:48:56-07:00Samantha Morinhlynka@uwindsor.caMyron Hlynkahlynka@uwindsor.caShan Xuhlynka@uwindsor.caA special customer must complete service from two servers, each with an $M/M/1$ queueing system. It is assumed that the two queueing systems have initiial numbers of customers $a$ and $b$ at the instant when the special customer arrives, and subsequent interarrival times and service times are independent. We find the expected total time (ETT) for the special customer to complete service. We show that even if the interarrival and service time parameters of two queues are identical, there exist examples (specific values of the parameters and initial lengths a and b) for which the special customer surprisingly has a lower expected total time to completion by joining the longer queue first rather than the shorter one.2017-09-20T00:00:00-07:00Copyright (c) 2017 Myron Hlynkahttp://www.ccsenet.org/journal/index.php/ijsp/article/view/70735Rasch Analysis and Functional Measurement in Post-Hospital Brain Injury Rehabilitation2017-10-13T02:48:57-07:00Frank D. Lewisfrank.lewis@neurorestorative.comGordon J. Hornfrank.lewis@neurorestorative.com<p><span style="font-family: 宋体; font-size: medium;">Rasch analysis is a statistical technique used in determining statistical properties of functional measures for use in research and treatment. The technique was used in the current study to determine the reliability and validity of the Mayo Portland Adaptability Inventory-Version 4 (MPAI-4) for use with three different acquired brain injury samples. Subjects were 777 adults (each group comprised of 259 individuals) with acquired brain injury treated in one of three rehabilitation program types: Neurorehabilitation (NR), Neurobehavioral (NB), or Supported Living (SL). The MPAI-4 was administered to each participant upon admission to program. Rasch analysis was conducted to assess item fit, reliability, and separation statistics for MPAI-4 assessments conducted within each program. Item difficulty values were examined to determine if the MPAI-4 differentiated among groups based on deficit profiles. The results revealed that for each group, fit statistics fell with appropriate levels (0.5 – 1.5) for at least 24 of 29 items. Rasch </span><em><span style="font-family: 宋体; font-size: medium;">person reliability</span></em><span style="font-family: 宋体; font-size: medium;"> statistics were 0.89 for NR and NB, and 0.90 for SL. </span><em><span style="font-family: 宋体; font-size: medium;">Item reliability</span></em><span style="font-family: 宋体; font-size: medium;"> was 0.99 for each of the groups. Item difficulty values accurately differentiated the three groups based on their specific deficit profiles expected. Specifically, NR participants’ greatest deficits demonstrated by the MPAI-4 were within cognitive and physical functions. For the NB participants, the greater deficits demonstrated were within the behavioral and adjustment items. Supported Living participants had the most limitation within the instrumental activities of daily living items. As in prior research findings, the current Rasch analysis supported the use of the MPAI-4 within this heterogeneous, acquired brain injury population. This unique statistical approach translates to treatment priorities that may assist clinicians with identifying treatment goals specific to unique treatment group characteristics (e.g., NR, NB, and SL). </span></p>2017-09-21T00:00:00-07:00Copyright (c) 2017 Frank D. Lewis, Gordon J. Hornhttp://www.ccsenet.org/journal/index.php/ijsp/article/view/70737Interval Estimation of Stress-Strength Reliability for a General Exponential Form Distribution with Different Unknown Parameters2017-10-13T02:48:57-07:00Nahed A. Mokhlisemad_j_ibrahim@yahoo.co.ukEmad J. Ibrahimemad_j_ibrahim@yahoo.co.ukDina M. Ghariebemad_j_ibrahim@yahoo.co.ukThis paper deals with interval estimation of the stress-strength reliability, when the stress and strength variables follow a general exponential form distribution. The distribution parameters of both the stress and the strength are assumed to be unknown. Interval estimation for reliability is discussed, using different approaches. The results obtained are applicable to many well known distributions. For illustration of the general results obtained a simulation study is performed with application on Weibull distribution. Numerical comparison of the interval estimators is carried out based on average length, probability coverage, and tail errors.2017-09-21T00:00:00-07:00Copyright (c) 2017 Nahed A. Mokhlis, Emad J. Ibrahim, Dina M. Ghariebhttp://www.ccsenet.org/journal/index.php/ijsp/article/view/70738Marshll–Olkin Extended Inverse Pareto Distribution and its Application2017-10-13T02:48:57-07:00M- GharibWesalagil@yahoo.comB-I- MohammedWesalagil@yahoo.comW-E-R- AghelWesalagil@yahoo.com<p><span lang="EN-US"><span style="font-family: 宋体; font-size: medium;">This paper introduces a new extension of the Inverse Pareto distribution along with in the framework of Marshal-Olkin (1997) family of distributions. This model is capable of modeling various shapes of aging and failure criteria. The statistical properties of the new model are discussed and the maximum likelihood and maximum product spacing’s methods are used to estimate the parameters involved. Explicit expressions are derived for the moments and the order statistics are examined for the new proposed model. Finally, the usefulness of the new model for modeling reliability data is illustrated using two real data sets with simulation study.</span></span></p>2017-09-21T00:00:00-07:00Copyright (c) 2017 M- Gharib, B-I- Mohammed, W-E-R- Aghelhttp://www.ccsenet.org/journal/index.php/ijsp/article/view/69932Analyzing the Customer Attrition using Survival Techniques2017-10-13T02:48:58-07:00Hasanthika, N. H. E.erandihasanthika@yahoo.comJayasekara, L. A. L. W.lesli@maths.ruh.ac.lk<p><span lang="EN-US"><span style="font-family: 宋体; font-size: medium;">Survival analysis techniques are used to study the amount of time between entry into observation and a subsequent event in estimating insurance attrition. Retention has always been a worldwide concern. A study is carried out on the profile of the policyholder and policies that produces better persistency based on one of the Sri Lanka experience using the nonparametric analysis (e.g. Kaplan-Meier estimator and life table analysis) and Cox regression model available through SPSS Statistics 20. This paper uses the survival model to evaluate the impact of covariates on the survival curves over a period of time. Newly opened life policies were considered during the period of 1st of January 2013 and 30</span><sup><span style="font-family: 宋体; font-size: small;">th</span></sup><span style="font-family: 宋体; font-size: medium;"> of June 2014 and our study period was end at 30</span><sup><span style="font-family: 宋体; font-size: small;">th</span></sup><span style="font-family: 宋体; font-size: medium;"> of June 2016. Survival analysis techniques can take into account for dealing with time-dependent variables and can help researchers to understand how insurance attrition impacts to the economic environment. Instead, the survival model provides much more information to the management and the people who deal with policies than what the regression model can offer. </span></span></p>2017-09-26T00:00:00-07:00Copyright (c) 2017 N.H.E. Hasanthika, L.A.L.W. Jayasekarahttp://www.ccsenet.org/journal/index.php/ijsp/article/view/70501On Heavy-tailed Crack Distribution for Loss Severity Modeling2017-10-13T02:48:58-07:00Taehan Baetaehan.bae@uregina.caJingjiao Chentaehan.bae@uregina.ca<div>Heavy-tailedness and right-skewness are two typical features of loss data resulting from catastrophic events such as storms or earthquakes. In this paper we study the tail properties of the generalized crack distribution which has recently been introduced as an extension of the Birnbaum-Saunders distribution and the three-parameter Gaussian crack distribution. The theoretical tail relationships between the auxiliary (or baseline) distribution and the resulting generalized crack distribution are studied relying on the classical theories of extreme values and regular variation. A few concrete examples of heavy-tailed crack distribution are constructed and used for model fitting exercises on both simulated and real catastrophic loss data sets. The fitting results show that the heavy-tailed crack distribution with an appropriate choice of baseline density function outperforms some other commonly used parametric models.</div>2017-10-04T00:00:00-07:00Copyright (c) 2017 Taehan Baehttp://www.ccsenet.org/journal/index.php/ijsp/article/view/70857Detection and Modeling of Asymmetric GARCH Effects in a Discrete-Time Series2017-10-13T02:48:58-07:00Emmanuel Alphonsus Akpaneubong44@gmail.comImoh Udo Moffateubong44@gmail.com<p class="1-Text">This study traced the patterns of discrete time series over time with respect to GARCH effect and asymmetric GARCH effect. Particularly, we paid attention to the weakness of the GARCH model in modeling the asymmetry of GARCH effect. In order to handle this weakness, we applied the sign and size bias test which comprises sign bias test, negative size bias test, positive size bias test, and Lagrange Multiplier test in order to identify the asymmetric effect in the residual series of the GARCH model. Where the asymmetric effect is present and significant, we fit the asymmetric GARCH models. Exploring the share price returns of Zenith bank plc obtained from the Nigerian Stock Exchange from January 4, 2006 to May 26, 2015, our findings indicated the presence of GARCH effect and was adequately captured by GARCH(0,1) model. Also, the sign and size bias test for asymmetric GARCH effect on the residual series of GARCH(0,1) model showed a joint significance as indicated by the Lagrange Multiplier test. Moreover, the asymmetric GARCH effect was adequately captured by EGARCH(0,1) and TGARCH(0,1) models. In addition, the significance of the size bias test indicated that the size of negative and positive returns has an impact on the predicted heteroscedasticity. Hence, we concluded that GARCH(0,1) model adequately predicted the GARCH effect but failed to capture the asymmetric effect in the share price returns of the discrete series. However, this was complemented by both EGARCH(0,1) and TGARCH(0,1) models with the size of both the negative and positive effects taken into consideration.</p>2017-10-11T00:00:00-07:00Copyright (c) 2017 Emmanuel Alphonsus Akpanhttp://www.ccsenet.org/journal/index.php/ijsp/article/view/71134A New Method for Logistic Model Assessment2017-10-13T02:48:58-07:00Di Shuwhe@stats.uwo.caWenqing Hewhe@stats.uwo.caIt is well known that the logistic model plays an important role for the analysis of binary outcomes. Most of the existing methods for the assessment of logistic models are constructed based on the distance between the observed and the predicted outcomes. We consider a new method from a different perspective by assessing the distance between two consistent estimators developed under the same logistic model form. The proposed tests are easy to implement and are applicable to both prospective and case-control studies.2017-10-12T00:00:00-07:00Copyright (c) 2017 Di Shu, Wenqing Hehttp://www.ccsenet.org/journal/index.php/ijsp/article/view/71167Unit Roots in Time Series with Changepoints2017-10-13T02:48:59-07:00Ed Herranzed.herranz@gmail.comJames Gentleed.herranz@gmail.comGeorge Wanged.herranz@gmail.comMany financial time series are nonstationary and are modeled as ARIMA processes; they are integrated processes (I(n)) which can be made stationary (I(0)) via differencing n times. I(1) processes have a unit root in the autoregressive polynomial. Using OLS with unit root processes often leads to spurious results; a cointegration analysis should be used instead. Unit root tests (URT) decrease spurious cointegration. The Augmented Dickey Fuller (ADF) URT fails to reject a false null hypothesis of a unit root under the presence of structural changes in intercept and/or linear trend. The Zivot and Andrews (ZA) (1992) URT was designed for unknown breaks, but not under the null hypothesis. Lee and Strazicich (2003) argued the ZA URT was biased towards stationarity with breaks and proposed a new URT with breaks in the null. When an ARMA(p,q) process with trend and/or drift that is to be tested for unit roots and has changepoints in trend and/or intercept two approaches that can be taken: One approach is to use a unit root test that is robust to changepoints. In this paper we consider two of these URT's, the Lee-Strazicich URT and the Hybrid Bai-Perron ZA URT(Herranz, 2016.) The other approach we consider is to remove the deterministic components with changepoints using the Bai-Perron breakpoint detection method (1998, 2003), and then use a standard unit root test such as ADF in each segment. This approach does not assume that the entire time series being tested is all I(1) or I(0), as is the case with standard unit root tests. Performances of the tests were compared under various scenarios involving changepoints via simulation studies. Another type of model for breaks, the Self-Exciting-Threshold-Autoregressive (SETAR) model is also discussed.2017-10-13T00:00:00-07:00Copyright (c) 2017 Ed Herranz, James Gentle, George Wanghttp://www.ccsenet.org/journal/index.php/ijsp/article/view/71298A Family of Non Linear Models in a Market with Semi Markov Regimes: Application to the Commodity and the Derivative Market2017-10-19T20:31:21-07:00Patrick Assonkenpassonken@coastalpines.eduGangaram S. Laddepassonken@coastalpines.eduThis paper introduces a family of coupled semi Markov regime switching multidimensional non linear models for general asset prices. Two particular instances of the models are explored. The first instance is one modeling commodity prices. Estimation formulas for historical parameters are developed. The second instance of the family of models introduced is one generalizing Heston model. It allows for semi Markov regime switching of Heston parameters. We develop a general semi closed formula for vanilla option prices given the risk neutral option parameters.2017-10-20T00:00:00-07:00Copyright (c) 2017 Patrick Assonken, Gangaram S. Laddehttp://www.ccsenet.org/journal/index.php/ijsp/article/view/71300Using Simple Alternative Hypothesis to Increase Statistical Power in Sparse Categorical Data2017-10-19T20:37:32-07:00Louis Mutterstkim@csumb.eduSteven B. Kimstkim@csumb.eduThere are numerous statistical hypothesis tests for categorical data including Pearson's Chi-Square goodness-of-fit test and other discrete versions of goodness-of-fit tests. For these hypothesis tests, the null hypothesis is simple, and the alternative hypothesis is composite which negates the simple null hypothesis. For power calculation, a researcher specifies a significance level, a sample size, a simple null hypothesis, and a simple alternative hypothesis. In practice, there are cases when an experienced researcher has deep and broad scientific knowledge, but the researcher may suffer from a lack of statistical power due to a small sample size being available. In such a case, we may formulate hypothesis testing based on a simple alternative hypothesis instead of the composite alternative hypothesis. In this article, we investigate how much statistical power can be gained via a correctly specified simple alternative hypothesis and how much statistical power can be lost under a misspecified alternative hypothesis, particularly when an available sample size is small.2017-10-20T00:00:00-07:00Copyright (c) 2017 Louis Mutter, Steven B. Kim