bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discrete software reliability growth models
Authors: Yamada Shioeru , Osaki Shunji 
Published: May 2007

AbstractA general description of a discrete software reliability growth model, which adopts the number of test runs or the number of executed test cases as the unit of error detection period, is presented. Two classes of discrete software reliability growth models are proposed and discussed. These models can be described by non‐homogeneous Poisson processes, in which the random variable is denned as the number of errors detected by n test runs (n = 0, 1, 2,…). The application and comparison of these models to actual software error data are shown.
The role of language in cross‐national surveys: American and Japanese respondents
Authors: Kuroda Yasumasa , Hayashi Chikio , Suzuki Tatsuzo 
Published: May 2007

AbstractBy using an ‘index of dissimilarities’, the present study demonstrates that certain questions and response categories worded in English and Japanese did not yield functionally equivalent responses in a series of surveys conducted in Japan and the United States among bilingual students. When students are thinking in Japanese, they are more likely to select a middle position response such as ‘it depends on…’ than when they are responding in English. The trend was observed among American students responding in Japanese as well. The study also analyses possible effects of cultural environment on response to survey questions through the use of Hayashi's ‘correspondence analysis’ technique.
Inequalities for stochastic flow shops and job shops
Authors: Pinedo Michael , Wie Sung‐Hwan 
Published: May 2007

AbstractConsider an m‐machine flow shop with n jobs. The processing time of job j, j = 1,…, n, on each one of the m machines is equal to the random variable Xj and is distributed according to Fj. We show that, under certain conditions, more homogeneous distributions F1,…, Fn result in a smaller expected makespan. We also study the effect of the variability of distribution Fj on the expected waiting costs of the n jobs and on the job sequencing which minimizes this total expected waiting cost. We show that the smallest (largest) variance first rule minimizes the total expected waiting cost on a single machine when the waiting cost function is increasing convex (concave). We also show that the smallest variance first rule minimizes, under given conditions, the total expected waiting cost in an m machine flow shop when the waiting cost function is increasing convex. Similar results are also obtained for the two‐machine job shop. Similar results cannot be obtained when the processing times of job j on the various machines are i.i.d. and distributed according to Fj.
An algorithm for nth degree stochastic dominance
Authors: Helms Billy P. , Jean William H. , Tehranian Hassan 
Published: May 2007

AbstractAn algorithm for nth degree stochastic dominance is developed using necessary conditions derived by Whitmore, Jean and Jean and Helms to reduce the computation time. The algorithm is presented and tested to determine run times for large sets of portfolios. The algorithm is fast enough computationally to be useful for both research projects and practical applications.
Structuring a regional problem: Aggregation and clustering in orderings
Authors: Owsiński Jan W. , Zadrozny Sławomir 
Published: May 2007

AbstractIn a planning effort for a region of Poland a problem structuring session was set up to assess the importance, imminence, and danger factor of issues arising through rapid development. These issues were ordered by a number of judges for the three features mentioned. An aggregation of these orderings was called for. Besides that, however, it was deemed necessary to perform clustering of issues, in view of the expected instability of aggregate orderings. For the aggregation of opinions the method developed by Marcotorchino and Michaud was used, paralleled by a modification of the method by Owsiński. Clustering was performed via a special LP formulation.
The population‐sample decomposition approach to multivariate estimation methods
Authors: Van Praag Bernard M. S. , De Leeuw Jan , Kloek Teun 
Published: May 2007

AbstractIn this paper it is argued that all multivariate estimation methods, such as OLS regression, simultaneous linear equations systems and, more widely, what are known as LISREL methods, have merit as geometric approximation methods, even if the observations are not drawn from a multivariate normal parent distribution and consequently cannot be viewed as ML estimators. It is shown that for large samples the asymptotical distribution of any estimator, being a totally differentiable covariance function, may be assessed by the δ method. Finally, we stress that the design of the sample and a priori knowledge about the parent distribution may be incorporated to obtain more specific results.It turns out that some fairly traditional assumptions, such as assuming some variables to be non‐random, fixed over repeated samples, or the existence of a parent normal distribution, may have dramatic effects on the assessment of standard deviations and confidence bounds, if such assumptions are not realistic. The method elaborated by us does not make use of such assumptions.
Interpretation of redundancy analysis: Rotated vs. unrotated solutions
Authors: Israëls A. Z. 
Published: May 2007

AbstractSome properties of redundancy analysis are summarized and suggestions for normalization are given. The relations between redundancy analysis and principal component analysis and, to a lesser extent, canonical analysis, are reasons for considering rotation techniques on the primary solution. An example from practice is given in which redundancy analysis is a useful technique, but where rotation of its results is desired in order to simplify the interpretation.
The estimation of stochastic cost‐quantity frontiers for discretionary cost and budgeted‐expenditure systems
Authors: Hamlen Susan S. , Hamlen William A. 
Published: May 2007

AbstractTwo alternative approximating functions for representing the unknown composite residual density function of a cost‐quantity frontier are examined. The frontier is one in which cost is regarded as preselected. This is appropriate for public sector economics and discretionary cost situations. One function requires the estimation of a single distribution parameter, whereas the other makes no a priori assumption on the shape of the density function.
Rankings aggregation in regional planning
Authors: Michaud Pierre 
Published: May 2007

AbstractThis paper proposes a solution to the Owsinsky and Zadrozny problem based on the Condorcet criterion. With this unique criterion and a unique approach it is possible to obtain either a collective ranking or clusters without using any distance. In both cases indices of conditioning can be associated. Also in both cases a very simple way (requiring practically no computation for this problem) to obtain the collective results will be given.
Group methodology in production management: A solution based on a hierarchical classification method
Authors: Lerman Israël‐César 
Published: May 2007

AbstractWe consider the problem submitted by Garcia and Proth and we propose for it a solution obtained by simply applying our very general method of hierarchical classification based on the likelihood of the links, in the case of an incidence table of data. This application is done on each of the two sides of the incidence data table. In our approach, the common number p of classes has not to be fixed arbitrarily, but is an observed possible result—provided by the notions of ‘significant’ levels and nodes of the classification tree—for the ‘natural’ association between two partitions. We compare our solution with the previous one.
A comparison of three linear rules for classification
Authors: Defays D. , Heuchenne C. 
Published: May 2007

AbstractThis paper compares three different linear procedures for classification: the normal one, the canonical one and a distribution‐free one recently described by Heuchenne. The study is mainly conducted using a simulation which makes it possible to compute the probabilities of correct allocation of the three methods in 3888 different cases. The normal rule looks slightly better than Heuchenne's, which looks clearly better than the canonical one. Finally, inference on Heuchenne's method is examined and conditions under which this method is optimal are given.
An application of some bayesian diagnostics to a study of the impact of blood lead upon human blood pressure
Authors: Atkinson S. E. , Crocker T. D. , Williams D. H. 
Published: May 2007

AbstractRecently, Pirkleet al.used a sample of 40–59 year old white males from the second cycle of the U.S. National Health and Nutrition Survey (NHANES II) to estimate the association between blood pressure and blood lead concentration. They found that, on average, a 1 μg/dl increase in blood lead increased diastolic blood pressure by about 4.5 per cent and systolic blood pressure by about 6.5 per cent. We use Bayesian diagnostics to enquire into the statistical robustness of some dimensions of their results. In particular, we ask whether the results they report are sensitive to specification uncertainty and are intolerant to measurement error. We conclude the possibility to be remote that the introduction or the omission of other covariates will significantly alter the estimated influence of blood lead upon either the diastolic blood pressures or the systolic blood pressures of the adult white males in their sample. Similarly, our analysis demonstrates that other covariates are likely to affect the estimated influence of blood lead concentration only if they are quite poorly measured.
Analysis of choice behaviour via probabilistic ideal point and vector models
Authors: Böckenholt I. , Gaul W. 
Published: May 2007

AbstractThe aim of this paper is to add results to the everlasting attempt to find appropriate models for the description and analysis of choice behaviour. As stochastic generalizations within choice models which allow estimation and testing in a straightforward way should be of great interest, probabilistic ideal point and vector approaches are used to handle inter‐ and intra‐individual irregularities in paired comparisons preference data. For choice behaviour analysis maximum likelihood estimates of the model parameters are computed and possibilities of testing various model variants by means of log‐likelihood ratio tests are discussed. The proposed models offer information to decide whether an ideal point or a vector approach is more appropriate for the description of the pairwise choice data. Examples of data sets known from previous research in choice behaviour are used for the comparison and for the demonstration of the merits of the proposed procedures.
Industry structure, performance and stability
Authors: Uri Noel D. 
Published: May 2007

AbstractThis paper looks at the issue once more of whether there is a statistically significant relationship between industry structure and economic performance. Tempered by the results of a test for structural stability, it is suggested that judicious choice of the industries included in the sample used to estimate the hypothesized relationship will lead to any desired result. As a consequence, one must be cautious in accepting the results of any study that unequivocally purports to show the presence or absence of an identifiable relationship between industry structure and industry performance.
A new stochastic ultrametric tree unfolding methodology for assessing competitive market structure and deriving market segments
Authors: Desarbo W. S. , de Soete G. , Carroll J. D. , Ramaswamy V. 
Published: May 2007

AbstractWe present a new methodology for simultaneously assessing competitive market structure and deriving market segments. A hierarchical or ultrametric tree representation is estimated in a maximum likelihood framework from collected paired‐comparison choice data. The derived tree portrays both brands and consumers/households/segments as terminal nodes, where the ‘closer’ a brand is to a particular consumer/household/segment in the tree, the higher the predicted probability of that consumer/household/segment choosing that particular brand. This paper initially presents an introduction to the problem of market structure assessment. We review the extensive marketing literature on market structure and survey several competing methodologies. The proposed stochastic ultrametric tree unfolding methodology is technically described and several program options are indicated. An illustration of the proposed methodology is presented with respect to paired comparison choice data collected from a convenience sample involving the over‐the‐counter analgesics market. Finally, several areas for future research are identified.
Markov: A methodology for the solution of infinite time horizon markov decision processes
Authors: Williams Byron K. 
Published: May 2007

AbstractAlgorithms are described for determining optimal policies for finite state, finite action, infinite discrete time horizon Markov decision processes. Both value‐improvement and policy‐improvement techniques are used in the algorithms. Computing procedures are also described. The algorithms are appropriate for processes that are either finite or infinite, deterministic or stochastic, discounted or undiscounted, in any meaningful combination of these features. Computing procedures are described in terms of initial data processing, bound improvements, process reduction, and testing and solution.Application of the methodology is illustrated with an example involving natural resource management. Management implications of certain hypothesized relationships between mallard survival and harvest rates are addressed by applying the optimality procedures to mallard population models.
Two‐state‐variable stochastic tree problems
Authors: Ye Meng‐Hua 
Published: May 2007

AbstractThis paper extends the one‐state‐variable stochastic tree problem to the two‐state‐variable case. (Considering, for example, a tree whose size and price evolve according to two different Wiener processes, we solve for the optimal cutting time. The optimization of the expected present discounted value of the tree is converted to a standard free‐boundary problem. Analytical results are reported. In particular we find that more variance near the optimal free boundary will increase the value of the tree. Finally, a method is developed to find the numerical solution to the free boundary problem. A numerical example is presented.
Application of a stochastic model to the breakage of flocs in stirred tanks
Authors: Nassar R. , Kim Y. H. , Glasgow L. A. , Fan L. T. 
Published: May 2007

AbstractA stochastic model is employed to account for the dynamic behaviour of floc breakage. More specifically, the evolution of the particle‐size distribution over time is presented. The model is compared to experimental data obtained by exposing kaolin—iron(III) flocs to hydrodynamic stress generated by a turbine impeller. The agreement between the model and experimental data appears to be satisfactory.
Relational analysis and dictionaries
Authors: Bedecarrax C. , Warnesson I. 
Published: May 2007

AbstractThe aim of the paper is to propose adequate models for the description of and appropriate solutions to dictionary optimization. A dictionary dedicated to human users is (as with any human artefact) full of errors and inconsistencies which cannot be handled by a computer as an end user. Thus, it is necessary to check and optimize the contents. By using ‘pairwise optimal clustering’ approaches, similarity aggregation and the new quadri‐decomposition methods, we will show how they are adapted to handle linguistic data in different configurations (a dictionary of synonyms and a bilingual dictionary). On these real‐life applications (i.e. our processed dictionary of synonyms corresponds to more than 2.5 billion matrix cells) we will describe how different aspects of such a method can be a good tool for designing new dictionaries for both applications.
A unified theory for coherent systems in reliability I. A generalization for some classic theory: Monotone binary coherent systems
Authors: Mazars N. 
Published: May 2007

AbstractBinary coherent system theory has played an important part in reliability. Its extension to (‘degradable’ or ‘multistate’ or) multinary systems has recently been considered in various papers, through various definitions. This paper lays the foundations of a unified theory for coherent systems by first giving unified arguments to apply and to investigate further binary and multinary systems. Monotone binary systems are introduced and examined by generalizing classic deterministic and probabilistic results. Applications of monotone coherence to the multinary case are proposed in a companion paper with a unified viewpoint on multinary coherent systems. As an indication, monotone constraints are defined with a partition of the component set and some total orderings imposed on the elements of the concerned partition. The discrete partition retrieves the classic theory of (free) binary coherent systems; some constraints defined from component levels lead to multinary coherent systems; some other constraints apply to systems submitted to some ‘common stresses’, e.g. the organizing system of a monotone coherent decomposition.
A unified theory for coherent systems in reliability II. A unified viewpoint on multinary coherent systems through monotone coherence and relevance
Authors: Mazars N. 
Published: May 2007

AbstractBinary coherent system theory has played an important part in reliability. Its extension to (‘degradable’ or ‘multistate’ or) multinary systems has recently been considered in various papers, through various definitions. This paper studies the most general model for multinary systems, proposes a unified viewpoint on multinary coherent systems and gives unified arguments to apply and to investigate further the binary and multinary cases.In a more detailed way, the ‘helpful bridge’ lately proposed by Block and Savits1 between the binary and multinary cases is completed and multinary systems then can be studied in terms of monotone binary coherent systems, introduced in a companion paper.2 Through various results, multinary systems are examined in terms of structure functions and of life functions; fundamental relations for their analysis are obtained with their set characterizations; the main axis that can be retained among the numerous types of coherence is emphasized, in a unified way, through relevance; reliability models are examined through performance processes, life lengths and performance functions; and Birnbaum's factors of importance are thoroughly extended to the multinary case. Fundamental results proposed in previous studies are thus completed with a shorter unified approach.
Analysis of pseudo‐periodic chronological series with irregularly time‐spaced data in view to their prediction. I. Proposed problem
Authors: Mennessier M. O. 
Published: May 2007

AbstractThe problem originates from the necessity to predict luminosities of large‐amplitude variable stars that are to be observed by the astronomical satellite HIPPARCOS. The data have a specific character: they are unequally time‐spaced and can be missing during a long time in comparison to the pseudo‐period. So the classical method of time‐series analysis must be adapted and new methods are to be searched.In the following papers we present two solutions: a numerical one derived from a Fourier analysis and a symbolic one.
Analysis of pseudo‐periodic chronological series with irregularly time‐spaced data in view to their prediction. III. Symbolic analysis
Authors: Mennessier M. O. , Diday E. 
Published: May 2007

AbstractThe problem originates from the necessity to predict luminosities of large‐amplitude variable stars that are to be observed by the astronomical satellite HIPPARCOS. The data have a specific character: they are unequally time‐spaced and can be missing during a long time in comparison to the pseudo‐period. So the classical method of time‐series analysis must be adapted and new methods are to be searched.In this paper we present a symbolic solution.
Analysis of pseudo‐periodic chronological series with irregularly time‐spaced data in view to their prediction. IV. Using a symbolic learning method
Authors: Quinqueton Joël 
Published: May 2007

AbstractWe first present briefly the CALM learning method, based upon the idea of belief. Then we state the multi‐agents scheme in which such a method can be used to predict numerical values. The basic idea is to simulate the expert's reasoning in front of a graphical display of the numerical values representing the phenomenon he wants to study:

First, looking at local shapes in the curve
Secondly, using maxima, minima and/or zero‐crossings to prevent long range errors in the prediction.
We present some results on the astronomy problem presented by M. O. Menessier about the prediction of brightness variation of Mira stars.
Combinatorial data analysis: Confirmatory comparisons between sets of matrices
Authors: Hubert Lawrence , Arabie Phipps 
Published: May 2007

AbstractThe task of assessing the similarity of pattern between the entries of two square matrices has been discussed extensively over the last decade, as a unifying strategy for approaching a variety of seemingly disparate statistical problems. As typically defined, the comparison depends on a measure of matrix correspondence, usually a normalized cross‐product measure of some form, that is evaluated for relative size by the use of a reference distribution constructed through an equally likely permutation hypothesis defined at the level of the objects corresponding to the rows and columns of the two matrices. The extreme generality provided by this very simple framework subsumes a variety of different statistical problems, ranging from the study of spatial autocorrelation for variables observed over a set of geographic locations, to the topics of analysis of variance, the measurement of rank correlation, and confirmation techniques concerned with various conjectures of combinatorial structure that might be posited for an empirically determined measure of relationship between pairs of a given set of objects. The comparison strategies extant always assume that both matrices are fixed, and in those cases where one of the matrices codifies a given theoretical structure to be evaluated according to a second, this assumption can lead to substantial arbitrariness in how matrix similarity might be indexed, and thus, in how the comparison is implemented. As developed in this paper, exactly the same principles appropriate for use in the fixed comparison context can be extended to include matrices constructed through optimally weighted linear combinations of other sets of matrices. This generalization provides one mechanism for developing comparison strategies that allow assessment against very broad classes of matrices, which in turn serve to represent very general conjectures of possible combinatorial structure. This paper reviews some of these extensions in detail, with a particular emphasis on categorical and ordered categorical variables and whether they may reflect an empirically generated measure of object relationship.
Granulocyte luminescence curves: Is anything there?
Authors: Kulesza Barbara , Owsiński Jan W. , Zadrożny Sławomir 
Published: May 2007

AbstractThis problem (proposed for the 4th International Symposium on Applied Stochastic Models and Data Analysis) concerns an exploratory study related to the presently accepted hypothesis that temporal curves of the forced pulse luminescence of specialized blood cells, granulocytes, may indicate the level of effectiveness of the immunological system. This paper presents a new set of empirical data and an analysis of its structure.