bluuebunny/crossref_metadata_2025_split huggingface dataset:
Whole blood viscosity and arterial thrombotic events in patients with systemic lupus erythematosus
Authors: Booth Stephanie , Chohan Saima , Curran James C. , Karrison Theodore , Schmitz Amanda , Utset Tammy O. 
Published: May 2007

AbstractObjectiveTo determine if whole blood viscosity (WBV), a rheologic variable contributing to risk of myocardial infarction and stroke in the general population, is elevated in patients with systemic lupus erythematosus (SLE), particularly SLE patients with a history of thrombotic or atherothrombotic events. Because the high rates of arterial and venous thrombosis in lupus cannot be explained by traditional risk factors, elevated WBV may be an easily measurable nontraditional risk factor to identify SLE patients at high risk for thrombotic events.MethodsSixty SLE patients (30 with a history of a thrombotic event) and 20 matched controls were recruited into the study. The thrombosis group was further subdivided into an arterial thrombosis group (n = 17). WBV values were determined at 9 different shear rates (1, 2, 5, 10, 50, 100, 150, 300, and 1,000 seconds−1). WBV was then compared between groups by repeated‐measures analysis of variance.ResultsSLE patients with a history of arterial events had significantly elevated WBV relative to either controls (P = 0.022) or SLE patients without arterial events (P = 0.014). WBV in the total SLE group did not differ from controls. Differences in WBV were most prominent at lower shear rates (1, 2, 5, 10, 50, and 100 seconds−1). Anticoagulation, prednisone dose, and antiphospholipid antibodies did not significantly impact WBV.ConclusionOur study demonstrated that WBV is selectively elevated in patients with SLE with a history of arterial events. Although this association is striking, longitudinal studies are needed to assess the positive predictive value of WBV for atherothrombotic events in SLE.
Exploratory data analysis for planar tessellations: Structural analysis and point process methods
Authors: Stoyan D. , Stoyan H. 
Published: May 2007

AbstractThis paper presents methods for the exploratory analysis of particular geometrical data, namely planar tessellations. At first, two non‐stochastic methods are suggested which may help to classify tessellations and to understand their structure. The first one consists of approximating a given tessellation by a Dirichlet tessellation. The other one uses the nodes of a given tessellation and tests the possibility of reconstructing it by a fixed rule of connecting nodes by edges.Furthermore, in order to obtain information on the spatial behaviour of a tessellation, we suggest the use of the methods of point process statistics. In particular, pair correlation and mark correlation functions describe spatial correlations in tessellations.
Comparison of some techniques of multidimensional scaling in soil fauna ecology
Authors: Al Ayoubi B. , Beninel F. , Le Calve G. 
Published: May 2007

AbstractThe aim of this paper is to propose some alternative solutions to a problem proposed by El‐Shishiny and Ghabbour, where the difficulty lies in vagueness rather than randomness. We first propose a city‐block analysis, undoubtedly better adapted to this type of problem than a Euclidean analysis. In the second part we develop a technique consisting in the decomposition of every distance Dij into two parts: the first, a star distance, considered as a personal effect; the second considered as a structure effect. These techniques are illustrated and compared in a real‐life example.
Ecological site classification: An application of clustering
Authors: Owsinski Jan W. , Zadrozny Sławomir 
Published: May 2007

AbstractThis short paper takes up the problem of El‐Shishiny and Ghabbour1 in order to highlight some of the problems in data analysis oriented at recognition of basic data structures, of hierarchy or partition type, with vagueness in initial data and/or the procedure applied. A response to the considered ‘soil fauna taxa versus Sudan sites’ problem is also suggested.
A general model of insurance and investment risk diversification
Authors: Page Dominique , Tremolieres Raymond 
Published: May 2007

AbstractThis article presents a model of insurance and investment risk diversification. An in‐depth analysis of the mathematical formulation of the risk is presented. In this regard, we introduce a new concept called the substitution principle to formulate the model rigorously. We show that, if the investment risks are normally non‐linear, the insurance risks are linear in nature. This proves that the well‐known diversification principle has to be viewed differently in finance and in insurance.
Semantics and factor analysis: An approach to the interpretation of factors
Authors: Lara B. F. , Tartas E. , Oyarzabal P. 
Published: May 2007

AbstractThe interpretation of factors constitutes a major problem in factor analysis. Until now the underlying semantic aspects of the question have been studied only occasionally. However, there are some indications that the mechanical interpretation of the results may constitute in the immediate future a real need in the realm of very large problems. On the other hand, the semantic study of multivariate statistical methods is the only way to warrant the validity of the mechanization procedures and the means to identify their limits.
Estimation of stress‐strength reliability based on tail‐modelling
Authors: Dargahi‐Noubary G. R. 
Published: May 2007

AbstractIn probabilistic design it is common to use parametric statistical models to calculate the probability of failure (Pf) obtained from stress‐strength interference theory. In this respect, it is well known that Pf is sensitive to the shape of the upper and lower tails of the stress and strength distributions respectively and also to their interference. If the true shapes of these tails could be discovered, it would be possible to improve the existing techniques. However, in practice there is seldom sufficient real data available to establish these tails with statistical significance. Moreover, often one or both variables are expensive to sample. Thus a separate tail estimation may not always be possible. Motivated to define a theoretical safety factor, the author presents a method here which provides a general solution to the problem by considering the tail estimation for a sample of increased sized. This is obtained by a reformulation of the problem in terms of excesses over a threshold, and by breaking the analysis into two parts; estimation of the number of exceedances and modelling the excesses. The analysis is carried out by non‐parametric estimation of the former and parametric modelling of the latter based on data from the critical region.
A unified theory for coherent systems in reliability part III: Two special cases for multinary systems—binary‐type coherence and homogeneous coherence
Authors: Mazars N. 
Published: May 2007

AbstractAs shown in a companion‐paper,1binary and multinary coherent systems can be studied with unified arguments, through monotone binary coherent systems. These are binary coherent systems submitted to some monotone constraint and generalize the classic theory of free binary coherent systems. By considering the unified point of view thus obtained, this paper gives what is perhaps the most suggestive representation for multinary coherent systems, since this extends the definition of binary coherent systems in terms of series‐parallel (parallel‐series) structures. Then, this paper examines the special case of multinary systems that can be studied directly with the classic theory of free binary coherent systems. It thus enlarges and complements, in a shorter unified manner, the particular cases considered in earlier studies.
Tracking models and the optimal regret distribution in asset allocation
Authors: Dembo Ron S. , King Alan J. 
Published: May 2007

AbstractWe present a tracking model for asset allocation that tracks desired investment goals. The model is shown to be optimal with respect to an investor's ‘regret distribution’, the cumulative distribution of the difference between the revenue under perfect foresight and that possible without foresight. Relationships with Markowitz mean/variance models are also explored.
New concepts and algorithms for portfolio choice
Authors: Dueck Gunter , Winker Peter 
Published: May 2007

AbstractThe paper studies the design of optimal (bond) portfolios taking into account various possible utility functions of an investor. The most prominent model for portfolio optimization was introduced by Markowitz. A real solution in this model can be achieved by quadratic programming routines for mean‐variance analysis. Of course, there are many reasons for an investor to prefer other utility criteria than return/variance of return in the Markowitz model. In the last few years, many efficient multiple purpose optimization heuristics have been invented for the needs in optimizing telephone nets, chip layouts, job shop scheduling etc. Some of these heuristics have essential advantages: they are extremely flexible and very easy to implement on computers. One example of such an algorithm is the threshold‐accepting algorithm (TA). TA is able to optimize portfolios under nearby arbitrary constraints and subject to nearly every utility function. In particular, the utility functions need neither to be convex, differentiable nor ‘smooth’ in any sense. We implemented TA for bond portfolio optimization with different utility criteria. The algorithms and computational results are presented. Under various utility functions, the ‘best’ portfolios look surprisingly different and have quite different qualities. Thus, for a portfolio manager it might be useful to provide himself with such a ‘multiple‐taste’ optimizer in order to be able easily to readjust it according to his own personal utility considerations.
Portfolio insurance and synthetic securities
Authors: Geman Hélyette 
Published: May 2007

AbstractThis paper aims to look at the situation of portfolio insurance, both from a theoretical and a practical standpoint, a decade after the methodology was first introduced by Leland and Rubinstein, and a few years after management strategies based on portfolio insurance were hurt by the crash of 1987. After a general introduction in Section 1, Section 2 presents a survey of different portfolio strategies and more specifically those related to portfolio insurance. Section 3 underlines the different issues raised by the market plunge of 1987, namely the problem of volatility misspecification, and studies the possible answers offered at this point by academics and practitioners. Section 4 contains some concluding comments.
Quadratic programming for portfolio optimization
Authors: Ho Diem 
Published: May 2007

AbstractPortfolio optimization is a procedure for generating a portfolio composition which yields the highest return for a given level of risk or a minimum risk for given level of return. The problem can be formulated as a quadratic programming problem. We shall present a new and efficient optimization procedure taking advantage of the special structure of the portfolio selection problem. An example of its application to the traditional mean‐variance method will be shown. Formulation of the procedure shows that the solution of the problem is vector intensive and fits well with the advanced architecture of recent computers, namely the vector processor.
Run orders and quantitative factors in asymmetrical designs
Authors: El Mossadeq A. , Koblinsky A. 
Published: May 2007

AbstractResults on run orders leading to trend‐free symmetrical factorial designs are extended to the asymmetrical case, using the character theory of abelian groups. The tools developed apply equally to the construction of designs for quantitative treatment factors with eight or more regularly spaced levels. Abelian group theory can also be used to find minimum‐cost run orders for asymmetrical designs, with a cost based on the number of changes of levels between successive runs.
On the generation of high‐quality white noise series
Authors: Figwer J. , Niederlinski A. 
Published: May 2007

AbstractA new approach to the simulation of white‐noise time‐series is presented. The approach is based on the frequency‐domain property of white‐noise as having a flat power spectrum density (PSD). From such a PSD, a linear complex spectrum of random‐phase multisinusoidal series (MS) may be generated. Next, the fast Fourier transform is applied to this linear spectrum to generate a random‐phase multisinusoidal N‐sample series, simulating the white‐noise series. The properties of some MS series are discussed including a gaussian white noise multisinusoidal series. The idea is illustrated by a number of examples. They demonstrate that the spectral and correlation properties of such series are enhanced in comparison to the properties of the random phases used to generate them. They also demonstrate that the spectral and correlation properties of such series are better, especially for short series, in comparison with standard white noise generators.
Stochastic models for the plastic rotation process in heat straightening of damaged steel plates
Authors: de Bejar Luis A. , Robinson Paul F. , Avent R. Richard 
Published: May 2007

AbstractTwo separate theoretical models are developed to predict the number of heat applications necessary to repair specified bends in damaged steel plates. One model is an application of the theory of reliability; this idealization is subsequently further simplified for practical engineering applications. The second is an application of the theory of stochastic processes: envisioning the record of plastic rotations obtained from the actual heat‐straightening of a subject plate as a finite portion of a member of the infinite ensemble of possible records for the repair, and assuming this process to be stationary and ergodic in the heat‐number domain, the theory of discrete spectral analysis is used to construct the power spectral density function of the process, and simulate artificial records. Then, simple statistical analysis allows the prediction with any desired degree of confidence. These independent probability‐based estimates successfully verify each other. As expected, the required number of repair heats for each test in the ensuing experimental program, under carefully controlled laboratory conditions, was consistently smaller than the corresponding theoretical prediction.
Job‐shop scheduling to minimize total waiting time
Authors: Chu Chengbin , Portmann Marie‐Claude 
Published: May 2007

AbstractThis paper addresses the job‐shop scheduling problem to minimize total waiting time. This also is equivalent to minimizing the work in process. Although, this problem is of relevance to manufacturing systems (Job‐shops), most of the work in the literature concerns the minimization of makespan for which the algorithms proposed are implicit enumeration procedures. For the minimization of total waiting time, to our knowledge, there are only empirical priority rules, all of which construct non‐delay schedules (i.e. there is no inserted idle time on the machines). In this work, we use theoretical results obtained for a single machine scheduling problem to construct an efficient heuristic for the problem at hand. This algorithm provides active schedules that are not always non‐delay schedules. The convergence and the complexity of the algorithm are discussed. The performance is also evaluated with respect to a classical priority rule.
The exploratory analysis of qualitative variables by means of three‐way analysis of two types of quantification matrices
Authors: Kiers Henk A. L. 
Published: May 2007

AbstractA comparison is made between a number of techniques for the exploratory analysis of qualitative variables. The paper mainly focuses on a comparison between multiple correspondence analysis (MCA) and Gower's principal co‐ordinates analysis (PCO), applied to qualitative variables. The main difference between these methods is in how they deal with infrequent categories. It is demonstrated that MCA solutions can be dominated by infrequent categories, and that, especially in such cases, PCO is a useful alternative to MCA, because it tends to downweight the influence of infrequent categories. Apart from studying the difference between MCA and PCO, other alternatives for the analysis of qualitative variables are discussed, and compared to MCA and PCO.
A mean reverting process for pricing treasury bills and futures contracts
Authors: Morgan Ieuan G. , Neave Edwin H. 
Published: May 2007

AbstractAn analytically tractable, discrete‐time single‐factor model is developed for valuing treasury bills and futures contracts. It uses a multiplicative binomial foward process that creates neither negative nor implausibly large positive interest factors, and which can incorporate different possible degrees of mean reversion. The paper derives explicit formulae for bill prices, futures prices, their conditional variances and risk premia in a setting that relates the evolution of the term structure more closely to both model and data than do other similar works. In contrast to other term‐structure constrained models, this paper emphasizes that in a one‐factor model the martingale probabilities cannot be treated independently of the perturbation functions. The paper's empirical methods also differ from the customary approaches. Instead of comparing differences between model‐predicted and observed prices, the paper applies ARCH methodology to test model‐predicted ratios of conditional variances to risk premia. Our tests find influences exogenous to the model, but these factors do not seem capable of being explained with two‐factor models using only interest rates.
The nature and extent of the geographic market for hogs in the United States
Authors: Uri Noel D. 
Published: May 2007

AbstractThis paper looks at the question of whether hogs sold at different locations in the United States are part of a single geographic market covering the entire country. An answer to this question is sought using an approach to defining a geographic market based on the notion of instantaneous causality. The empirical results, based on prices for hogs at sixteen different locations over the period October 1989 to May 1992, suggest that there was but a single identifiable geographic market covering the entire United States. The implications of this finding are explored.
Information theory approach in efficiency measurement
Authors: Sengupta Jati K. 
Published: May 2007

AbstractThe current non–parametric method of measuring productive efficiency of input–output systems is generalized here in the stochastic case in terms of an information theory approach based on the concept of entropy. Use of maximum entropy as a method of finding the most probable distribution of the input–output data set and as a predictive criterion is illustrated for production systems with multiple inputs and outputs.
Bounds on stochastic convex allocation problems
Authors: Edirisinghe Chanaka , Atkins Derek , Iyogun Paul 
Published: May 2007

AbstractWe consider a stochastic convex program arising in a certain resource allocation problem. The uncertainty is in the demand for a resource which is to be allocated among several competing activities under convex inventory holding and shortage costs. The problem is cast as a two–period stochastic convex program and we derive tight upper and lower bounds to the problem using marginal distributions of the demands, which may be stochastically dependent. It turns out that these bounds are tighter than the usual bounds in the literature which are based on limited moment information of the underlying random variables. Numerical examples illustrate the bounds.
Non–parametric probability density function estimation on a bounded support: Applications to shape classification and speech coding
Authors: Saoudi S. , Hillion A. , Ghorbel F. 
Published: May 2007

AbstractIn statistics, it is usually difficult to estimate the probability density function from N independent samples X1,X2, …︁, XN identically distributed. A lot of work has been done in the statistical literature on the problem of probability density estimation (e.g. Cencov, 1962; Devroye and Gyorfi, 1981; Hall, 1980 and 1982; Hominal, 1979; Izenman, 1991; Kronmal and Tarter, 1968; Parzen, 1962; Rosenblatt, 1956). In this paper, we consider random variables on bounded support. Orthogonal series estimators, studied in detail by Kronmal and Tarter (1968), by Hall (1982) and by Cencov (1962), show that there is a disadvantage related to the Gibbs phenomenon on the bias of these estimators. We suggest a new method for the non–parametric probability density function estimation based on the kernel method using an appropriately chosen regular change of variable. The new method can be used for several problems of signal processing applications (scalar or vector quantization, speech or image processing, pattern recognition, etc.). Applications to shape classification and speech coding are given.
Behaviour of queueing approximations based on sample moments
Authors: Johnson Mary A. , Luhman Jennifer A. 
Published: May 2007

AbstractWe investigate moment–based queueing approximations in the presence of sampling error. Let L be the steady–state mean number in the system for a GI/M/1 queue. We focus on the estimation of L under the assumption that only sample moments of the interarrival–time distribution are known. A simulation experiment is carried out for several interarrival–time distributions. For each case, sample moments from the interarrival–time distribution are matched to an approximating phase–type distribution and the corresponding estimate L is obtained. We show that the sampling error in the moments induces bias as well as variability in L. Based on our simulation experiment, we suggest matching only two moments when the sample coefficient of variation is low or when sample size is low; otherwise, matching three moments is preferable.
A multivariate stochastic model with non‐stationary trend component
Authors: Kato Hiroko , Naniwa Sadao , Ishiguro Makio 
Published: May 2007

AbstractThe purposes of this paper are to introduce a multivariate non‐stationary stochastic time series model without individual detrending and to extract the multiple relationships between variables. To infer the statistical relation between variables, we attempt to estimate the co‐movement of multivariate non‐stationary time series components. The model is expressed in state‐space form, and time series components are estimated by the maximum likelihood method using numerical optimization algorithm. The Kalman filter algorithm is used to compute the likelihood of the model. The AIC procedure gives a criterion for selecting the best model fit for the data. The multiple relationship becomes clear by analysing estimated AR coefficients. Real economic data are used for a numerical example.
Semi‐parametric estimation of covariate effects using the positive stable frailty model
Authors: Wang S. T. , Klein John P. , Moeschberger M. L. 
Published: May 2007

AbstractMany biological and medical studies have as a response of interest the time to occurrence of some event, such as the occurrence of a particular symptom or disease, remission, relapse, death due to some specific disease, or simply death. In this paper we study the problem of assessing the effect of potential risk factors on the outcome event of interest through a parametric or semi‐parametric frailty model where the lifetimes have a reason to be considered dependent. This dependence may arise because of multiple endpoints within the same individual or because, when studying a single endpoint, there are natural groupings between study subjects. The objective of this paper is to extend both parametric and semi‐parametric approaches to regression analysis in which the lifetimes of individuals in a group are effected by the same random frailty which follows a positive stable distribution. Some comparisons of the properties of this frailty distribution with other frailty distributions are made and an example which assesses the effect of a treatment in a litter‐matched tumorigenesis study is presented.