bluuebunny/crossref_metadata_2025 huggingface dataset:
An Application of a Displaced Poisson Process*
Authors: Clarkson D.B. , Wolfson D.B.
Published: April 2008

Abstract  A displaced Poisson process is presented as a reasonable model in describing the stages of certain chronic diseases. Although in some respects the model is an oversimplification of the true picture its feature is that it facilitates the easy estimation of some of the important parameters that arise in this area. Among the quantities estimated are the mean lead time and the distribution function of the time spent in the preclinical state. Properties of some of the estimators are obtained.
Monotone empirical Bayes estimators for the continuous one‐parameter exponential family
Authors: Houwelingen J.C. van , Stijnen Th.
Published: April 2008

Abstract  A class of empirical Bayes estimators (EBE's) is proposed for estimating the natural parameter of a one‐parameter exponential family. In contrast to related EBE's proposed and investigated until now, the EBE's presented in this paper possess the nice property of being monotone by construction. Based on an arbitrary reasonable estimator of the underlying marginal density, a simple algorithm is given to construct a monotone EBE. Two representations of these EBE's are given, one of which serves as a tool in establishing asymptotic results, while the other one, related with isotonic regression, proves useful in the actual computation.
Analysis of variance on indirectly measured variables
Authors: Engel J.
Published: April 2008

Abstract  When observations from a normal distribution can only be obtained indirectly by counting the number of subjects responding to a previously chosen dose, parameter estimates can be obtained by using probit analysis. Well‐known is the maximum likelihood technique of parameter estimation, less known is the approach by weighted least squares. The latter approach is followed to compare the parameters of several normal distributions by testing their equality, in analogy with the analysis of variance. A practical situation gave rise to this study and it is worked out at the end of the paper.
Relative efficiency and deficiency of kernel type estimators of smooth distribution functions
Authors: Falk M.
Published: April 2008

Abstract  The problem is investigated whether a given kernel type estimator of a distribution function at a single point has asymptotically better performance than the empirical estimator. A representation of the relative deficiency of the empirical distribution function with respect to a kernel type estimator is established which gives a complete solution to this problem. The problem of finding optimal kernels is studied in detail.
Statistical survival analysis of male larynx‐cancer patients ‐ a case study
Authors: Kardaun O.
Published: April 2008

Abstract This paper deals with a concrete case: Of 90 male larynx‐cancer patients, diagnosed and treated in the period 1970–1978, either the survival time or, if the patient was still alive at the end of the study, an appropriate lower bound on it was recorded. One factor (stage of the cancer) and one covariate (age of the patient) were a priori selected as important variables possibly influencing the survival function.

After an elementary analysis of the 3 and 5 year survival fractions in section 2, a nonparametric estimation of the survival functions ignoring the effect of age is presented in section 3. In the last section COX'S (1972) proportional hazards model is used for a one dimensional regression on age which leads to the estimation ofSi(tz), the survival function of patients with stageiand agez. This allows for a graphical comparison with the normal population. Finally some checks on the proportional hazard assumption are performed.

The emphasis in this paper is on adequately applying and adapting (mostly existing) techniques, including the use of some generally available computer programs, to a practical case. Care has been given to model assumptions and theoretical foundations of the relevant methods.
The informative sample size for dynamic multiple equation systems with moving average errors
Authors: Tigelaar H. H.
Published: April 2008

Abstract  The problem considered here, is that of finding suitable conditions for dynamic economic systems that exclude the existence of observationally equivalent structures. Here observational equivalence refers to equality of distributions or first and second moments of a small finite sample from the observable process. It is shown, that under these conditions we may act as if the lagged endogenous variables are nonrandom exogenous variables, when global identifiability is investigated.
MAXIMUM ENTROPY REVISITED
Authors: Mukherjee D. , Hurst D. C.
Published: April 2008

Maximum entropy or minumum information distributions have their flexibilities severely curtailed if R or R+ is the domain and α is imposed as a Lebesgue measure. Tremendous flexibility is gained by removing these restrictions.
AN APPROXIMATE CONFIDENCE INTERVAL FOR THE DIFFERENCE BETWEEN QUANTILES IN A BIO‐MEDICAL PROBLEM
Authors: Albers Willem , Löhnberg Peter
Published: April 2008

In this note it is described how two distributions arising in a bio‐medical investigation are compared by means of a confidence interval for the difference of appropriate quantiles. It is briefly indicated how an approximation for such a confidence interval is derived.
HODGES‐LEHMANN EFFICACIES FOR LIKELIHOOD RATIO TYPE TESTS IN CURVED BIVARIATE NORMAL FAMILIES
Authors: Brown L. D. , Ruymgaart F. H. , Truax D. R.
Published: April 2008

For hypothesis testing in curved bivariate normal families we compare various size a tests by means of their Hodges‐Lehmann efficacies at fixed alternatives, in particular when these tests have equal optimal asymptotic power in the local Pitman sense. The locally most powerful tests and the likelihood ratio tests for the curve are both Pitman optimal, but the latter turn out to have higher Hodges‐Lehmann efficacy. All the tests considered here, including the locally most powerful tests, are likelihood ratio tests against suitable (possibly enlarged) sets of alternatives, the curve itself being an important special case of such a subset. In passing we illustrate a general result in Brown (1971) concerning Hodges‐Lehmann optimality obtained by enlarging the model.
RIDIT ANALYSIS, A REVIEW
Authors: Jansen Marlies E.
Published: April 2008

In ridit analysis scale values are assigned to the categories of an ordinal response variable, the ridits. Ridit analysis is described as a technique to compare groups of observations and to measure the association between ordinal and nominal variables by mean ridits. By their definition mean ridits are closely related to distribution‐free methods. Mean ridits are also used as a tool to test the main and/or interaction effects of factors on an ordinal response variable.
A COMPARISON OF THE POWERS OF A GENERALIZED FRIEDMAN'S RANK TEST AND AN ALIGNED RANK PROCEDURE BASED ON SIMULATION
Authors: de Kroon J. , van der Laan P.
Published: April 2008

This paper presents the results of an experimental determination by Monte Carlo techniques of the power functions of a generalized Friedman's rank test based on “standardized” ranks and a proposed test procedure based on aligned ranks for orthogonal designs. The simulation is carried out for five orthogonal designs and a number of Normal location alternatives and gives some information about the difference in power of the two test procedures for some orthogonal designs.
BAYESIAN ESTIMATION OF T–G RIDGE MODEL
Authors: Saxena Ashok K.
Published: April 2008

Ridge type analysis of the Theil–Goldberger mixed model, considered earlier by Saxena and Bhatta–charya (1983) for the non–Bayesian set–up, is discussed from the Bayesian view–point when a has a closed prior and the loss–function being squared error.
RANDOM WALKS ON REGULAR POLYHEDRA AND OTHER DISTANCE–REGULAR GRAPHS
Authors: van Slijpe A.R.D.
Published: April 2008

In this paper we consider Markov chains of the following type: the state space is the set of vertices of a connected, regular graph, and for each vertex transitions are to the adjacent vertices, with equal probabilities. When the mean first–passage matrix F of such a Markov chain is symmetric, the expectation and variance of first–entrance times, recurrence times, number of visits to a vertex and the expectation of the number of different vertices visited, can easily be computed from the entries of F. The method is most effective, when the underlying graph is distance–regular; then F is symmetric and the entries of F can easily be obtained from the graph.
SOME SMALL–SAMPLE NON–PROPORTIONAL HAZARDS RESULIS FOR THE KAPLAN–MEIER ESTIMATOR
Authors: Geurts J.H.J.
Published: April 2008

CHEN, HOLLANDER and LANGBERG (1982) presented exact small–sample results for the KAPLAN–MEIER (1958) estimator under the proportional hazards model. We present simulation results for the same estimator for small samples in a number of cases where the hazard rates are not proportional. These suggest that the proportional hazards results, especially with regard to the Mean Square Error, are typical for a fairly large variety of “non–proportionalities” that may be encountered in practice. Thus the MSE of the KAPLAN–MEIER estimator appears to be rather robust against deviations from proportionality of the survival and censoring hazard rates. We illustrate the practical importance of this property by two examples.
ON THE ANALYSIS OF VARIANCE FOR BETA – BINOMIA
Authors: Engel J.
Published: April 2008

The beta–binomial distribution is reported in literature as a useful generalization of the binomial in case of heterogeneous binomial sampling. An extra model parameter is introduced to accommodate for extra–binomial variation. Some additions to results already available will be given by presenting approximate F–tests for factorial designs, where the response variable is of 0–1 type and sampling is heterogeneous binomial. These tests can be used when sample sizes are large and equal and some degrees of freedom are left from replicates or negligible interactions to estimate the extra model parameter.
INVARIANCE OF THE UNORDERED BEST ESTIMATOR IN THE T,–CLASS FOR MIDZUNO'S AND FOR IKEDA–SEN'S SAMPLING PROCEDURES
Authors: Prabhu–Ajgaonkar S.G. , Shah S.M.
Published: April 2008

MIDZUNO'S sampling procedure is considered where the first (n – 1) draws are carried out with simple random sampling without replacement and the nth draw with varying probabilities. It is shown that for this scheme, the best estimator in the HORVITZ–THOMPSON (1952) Tt–class of linear estimators exists and rejects the last draw. When MURTHY'S technique of unordering of an ordered estimator is employed, the rejected draw is restored and the unordered estimator is obtained. Surprisingly, this unordered estimator is the same as the unordered best estimator in the T1–class, derived for IKEDA–SEN'S sampling procedure.
THE “VEREENIGING VOOR DE STATISTIEK”, 1857–1892
Authors: Stamhuis I.H.
Published: April 2008

This paper deals with the history of the nineteenth century Dutch statistical society: “Vereeniging voor de Statistiek”, founded in 1857. In the second half of the nineteenth century the society flourished and had a considerable amount of members. It played a very active role for the establishment of a central official statistical bureau: “Centraal Bureau voor de Statistiek”. These activities ended with success in 1892. Then the society changed its name and did no longer engage itself with statistics. Members of the statistical society thought of statistics as facts about society, mostly numerical, but not always. They hoped to discover the laws which ruled society, by means of statistics. In that way the social sciences would improve.
STOCHASTIC INTEGER PROGRAMMING BY DYNAMIC PROGRAMMING
Authors: Lageweg B.J. , Lenstra J.K , RinnooyKan A.H.G. , Stougie L. , Kan A.H.G. Rinnooy
Published: April 2008

Stochastic integer programming is a suitable tool for modeling hierarchical decision situations with combinatorial features. In continuation of our work on the design and analysis of heuristics for such problems, we now try to find optimal solutions. Dynamic programming techniques can be used to exploit the structure of two–stage scheduling, bin packing and multiknapsack problems. Numerical results for small instances of these problems are presented.
THE CHOICE OF CELLS IN CHI–SQUARE TESTS
Authors: Oosterhoff J.
Published: April 2008

The choice of cells in chi–square goodness of fit tests is a classical problem. Some recent results in this area are discussed. It is shown that the likelihood ratio of alternatives w.r.t. null distributions plays a key role when judging different procedures. The discussion centers on the case of a simple hypothesis, but location–scale models and tests of independence in contingency tables are also considered.
STATISTICS IN THE SOCIAL AND BEHAVIORAL SCIENCES
Authors: Molenaar I.W.
Published: April 2008

This survey paper gives an impression of the main ways in which statistics is used in disciplines such as sociology and psychology. After an introductory section 1 the negative image of social science research is discussed in section 2. Section 3 is devoted to the enormous influence of modern computing facilities. Measurement of human behaviour has its specific problems (section 4). The use of linear and log–linear models is the topic of section 5. Latent variables are a basic concept for social and behavioral scientists, both in some linear models (section 6) and in item response theory (section 7). In the next section multidimensional and optimal scaling techniques are mentioned, and a selection of other topics is the content of section 9. Some general remarks on the generalizability claim of statistical methods constitute the final section. Because of space limitations and priority considerations, the author has decided to write a paper about topics and not about individual research contributions. For this reason there is no list of references (it would take several pages) and no painful split of all Dutch authors into those mentioned and those omitted. In general the Dutch research community has made quite a few major contributions to the area discussed in this paper.
MARKOV DECISION PROCESSES
Authors: van der Wal J. , Wessels J.
Published: April 2008

A review is presented of the development over the years of the theory and practical use of Markov decision processes. To this purpose three periods are considered: before 1966, from 1966 till 1972, and after 1973. In all 3 periods there has been some contribution from the Netherlands, but particularly in the last period the research in the Netherlands on the subject has become a major stream. In this review particular emphasis is given to the work which has been done in the Netherlands, but the main line of the paper is determined by the development of the applicability of the available theory.
CENTRAL LIMIT THEORMS IN C[0,1] FOR A CLASS OF ESTIMATORS OF A DISTRIBUTION FUNCTION
Authors: Nixdorf R.
Published: April 2008

As non–parametric estimates of an unknown distribution function (d.f.) F based on i.i.d. observations X1 Xn with this d.f.

are used, where Hn is a sequence of d.f.'s converging weakly to the unit mass at zero. Under regularity conditions on F and the sequence (Hn) it is shown that √n(Fn–F) and √n(Rn– F) in C[0,1] converge in distribution to a process G with G(t) =W° (F(t)), where W° is a Brownian bridge in C[0,1]. Further the a.s. uniform convergence of R., is considered and some examples are given.
SOME METHODOLOGICAL ASPECTS OF ESTIMATING THE FIRST FEW MOMENTS OF THE DISTRIBUTION OF THE GAMMA RAY MULTIPLI
Authors: BRON K. , KOSSE B. , POORTEMA K. , SCHAAFSMA W. , de VOIGT M.J.A. , WERF S.Y. VAN DER
Published: April 2008

The non–identifiability of relevant parameters is often used as a decisive argument to reject the mathematical model and (or) experimental design. This study shows by means of an example that the argument is not compelling. The experiment to be considered has been designed to determine the first few moments of the distribution of the number of gamma rays, emitted after a nuclear fusion reaction of a particular type. This task of determining moments is so complicated that certain systematic errors cannot be completely avoided. In consequence, the moments are not identifiable with respect to the usual mathematical model and the current experiment (section 2). There is no sense in rejecting the model or the experiment on the basis of this non–identifiability. It is easy to construct a simple estimator for the first moment, with properties that are not too bad (section 2). The current estimation procedures seem to be more accurate. They can even be used to estimate some higher moments. The systematic errors cannot be avoided but are negligible in many reasonable situations (section 3 and 4).

The actual analysis of the data is more complicated than suggested in the first four sections. Nevertheless these sections are relevant because the underlying model gives an adequate description of the observations after a preliminary reduction of the data. This fact is intuitively clear but can also be proved (section 5).

A test–case suggests that even the standard errors provided by the current technology are reliable (section 6).
A LIMIT THEOREM FOR BERNOULLI RV'S AND FELLER'S SHOE PROBLEM
Authors: Dwass M.
Published: April 2008

Consider n sets of objects, each set consisting of m distinct types (for instance n place settings each made up of m distinct dishes and silverware pieces.) s items are drawn at random from the mn items. The distribution of the number of complete sets (each consisting of all m items) in the sample of s is asymptotically Poisson distributed with parameter (a /m)m if s = an1–1 and n→∞. This fact can be interpreted in terms of a certain limit theorem for a sequence of i.i.d Bernoulli rv's.
ON BOOTSTRAPPING A CLASS OF DIFFERENTIABLE STATISTICAL FUNCNONALS WITH APPLICATIONS TO L– AND M– ESTIMATES
Authors: Yang S–S.
Published: April 2008

EFRON'S (1979) “bootstrap” method is justified for a class of differentiable statistical functionals which includes many L– and M–statistics. For illustration, a Monte Carlo study for the trimmed means is also included.
CHARACTERIZING THE NORMAL DENSITY AS A SOLUTION OF A DIFFERENTIAL EQUATION
Authors: Hombas V. C.
Published: April 2008

This note shows how we can characterize the normal density using a differential equation.
LINEAR TREND TEST VERSUS GLOBAL TEST: A COMPARISON
Authors: Rothe G.
Published: April 2008

For the I–sample problem, the classical global tests on treatment differences are compared with the respective trend tests both in the parametric and nonparametric case using a comparison criterion closely related to the concept of asymptotic relative Pitman efficiency.
A NOTE ON SAMPLING WITH AND WITHOUT REPLACEMENT
Authors: Stam A.J.
Published: April 2008

Upper bounds are given for the total variation distance between the distribution statistics of random samples with and without replacement from a finite set.
MODEL REFERENCE ADAPTIVE SYSTEM ESTIMATES FOR COUNTING PROCESSES
Authors: Thavaneswaran A.
Published: April 2008

The adaptive estimation procedure of the model reference adaptive system is modified and applied to counting process models. Maximum likelihood estimates constitute a subclass of the adaptive estimators considered. The adaptive estimator is shown to be strongly consistent and to converge in law to a normal variate. Applications are considered; for example properties of the adaptive estimate are obtained for a periodic intensity model.
CHANGE–OVER TRIALS WITH BINARY DATA: ESTIMATION
Authors: Fidler V.
Published: April 2008

Abstract. Estimation of success rates in the two–period change–over clinical trial with binary responses is considered under a mixed model for the design.
CONSTRAINED NON–LINEAR LEAST SQUARES
Authors: Don F. J. H.
Published: April 2008

Abstract. Asymptotic properties of the constrained non–linear least squares estimator and the associated Lagrangian multipliers are derived, extending the results of LOTKEPOHL (1983).
Recent PH.D. Theses in The Netherlands
Authors: EINMAHL J.H.J.
Published: April 2008

Statistica Neerlandica has decided to encourage the reporting on theses in probability, statistics, biometrics, econometrics and operations research, submitted to Dutch universities. The main purpose of this section is to inform the reader briefly of the nature, the practical and theoretical importance, the methods used and the results presented in recent theses. It is understood that contributions to this section meet with the approval of the supervisor(s) of the thesis.
Waiting Time Distribution for a Semaphone System
Authors: Wallin J.F.E.
Published: April 2008

A queueing system is considered, that is representative for the serving of semaphone calls in the Netherlands.

First the model is generalized and formulae for the waiting time distribution and the mean waiting time are derived. Two special cases are considered: the first one being a simplification of the actual system of the Dutch PTT, the second one being the real situation.

Cumulative waiting time distributions and mean waiting times are calculated, the distributions are plotted.
Monotonicity of Rank Statistics in some Non–parametric: Testing Problems
Authors: Schriever B.F.
Published: April 2008

For some non–parametric testing problems (one–sided two–sample problem, k–sample trend problem, testing independence against positive dependence) a partial ordering, denoted by ≥, over the alternatives is defined. This partial ordering expresses the strength of the deviation from the null–hypothesis. All familiar rank tests turn out to become more powerful under “increasing” alternatives; that is, all familiar rank statistics preserve the ordering stochastically in samples whenever it is present between underlying distributions. As a tool, the sample equivalence of ≥ is introduced as a partial ordering over pairs of permutations. Functions, defined on pairs of permutations, which preserve this ordering are studied.
Partial Minimax Estimation in Regression Analysis
Authors: Hering F. , Trenkler G. , Stahlecker P.
Published: April 2008

The general minimax estimator of the linear regression model is applicable when the whole parameter vector is restricted to an ellipsoid. In many applications, however, it is more realistic to assume that only a part of the parameter set is constrained. For this case an alternative minimax approach is developed.
Distributional Properties of Record Values from the Geometric Distribution
Authors: Ahsanullah M. , Holland B.
Published: April 2008

Some distributional properties of the record values of non–identically distributed random variables having geometric distributions are discussed. Three theorems dealing with the characterization of the geometric distribution based on these distributional properties are presented. The unique minimum variance unbiased estimators of some functions of the parameters of the distribution and various predictors of the s–th record valued utilizing the first m(m<s) record values are studied.
Regression with errors in variables: estimators based on third order moments
Authors: van Montfort K. , Mooijaart A. , de Leeuw J.
Published: April 2008

In this paper consistent and, in a well–defined sense, optimal moment–estimators of the regression coefficient in a simple regression model with errors in variables are derived. The asymptotic variance and other asymptotic properties of these estimators are given. As is known for a long time, serious estimation problems exist in this model. There are two ways out of this problem: using either additional assumptions or additional information in the data. A lot of attention has been paid to the use of additional assumptions. However, quite often this leads to rather unrealistic models. In this paper we use additional information in the data. That means here that, besides first and second order moments, third order moments are formulated as functions of the model parameters. Besides theoretical derivations a small study with generated data is discussed. This study shows that for samples larger than 50 the estimates we consider behave nicely.
On the Distribution of General Quadratic Functions in Normal Vectors
Authors: de Gunst M.C.M.
Published: April 2008

A representation in terms of independent standard normal variables tor the general quadratic form in normal variables in the univariate case, obtained by DIK and DE GUNST (1985), is extended to the multivariate situation. A representation for the quadratic function in normal vectors X'AX, where X is a random matrix with normally distributed elements and A a real symmetric matrix, is given in terms of independent and identically distributed central normal vectors. The representation is valid only when the covariance structure of X is of a special form, but all known results, especially necessary and sufficient conditions for X'AX to have a Wishart distribution, can easily be derived from it.
Data analysis and statistics, report of a discussion
Authors: de Gruijter D.N.M.
Published: April 2008

A report is given of a discussion by De Leeuw, Molenaar, and audience on the role of models and generalization in statistical inference.
Note on discrete a‐unimodality
Authors: Steutel F.W.
Published: April 2008

An interpretation is given of ABOUAMMOH'S (1987) discrete analogue of the (one‐dimensional) definition of a‐unimodality by Olshen and Savage. The concepts are of some interest in the context of selfdecomposability.
The De Mortibus distribution and variability of biological magnitudes
Authors: Timmer E.
Published: April 2008

The DM distribution is a one parameter family of logistic/log‐logistic distributions that was found empirically in comparative epidemiological research in the then Laboratory of Hygiene of the University of Amsterdam (project DE MORTIBUS Agez 3). It is of interest for mathematical statistics as a new family of distributions and for biology as a contribution to the understanding of variability and as a guide in goal‐directed experiments.
Logistic Regression, a review
Authors: van Houwelingen J.C. , le Cessie S.
Published: April 2008

A review is given of the development of logistic regression as a multi‐purpose statistical tool.

A historical introduction shows several lines culminating in the unifying paper of Cox (1966), in which theory as developed in the field of bio‐assay is shown to be applicable to designs as discriminant‐analysis and case‐control study. A review is given of several designs all leading to the same analysis. The link is made with epidemiological literature.

Several optimization criteria are discussed that can be used in the case of more observations per cell, namely maximum likelihood, minimum chi‐square and weighted regression on the observed logits. Recent literature on the goodness of fit problem is reviewed and finally, comments are made about the non‐parametric approach to logistic regression which is still in rapid development.
Logit based parameter estimation in the Rasch model
Authors: Verhelst N. , Molenaar I.W.
Published: April 2008

The similarities between the logistic regression model and the Rasch model (used in psychometric item response theory) are used to derive several methods based on logits that produce parameter estimates for the Rasch model. A result from LeCam and Dzhaparidze is used by which an initial consistent estimate is transformed by one scoring method iteration into an estimate that has the same asymptotic efficiency as the (in this case conditional) maximum likelihood estimate of the item parameters. Indirect evidence about the bias of this CML estimator is produced by studying the (more easily derived) bias of the estimator based on the unweighted logits. Finally, some simple weighted least squares logit‐based estimates are presented, and their performance is assessed. On the whole, the computationally simpler logit‐based estimates give a fairly good approximation to the CML estimates.
Statistics of extremes in climatology
Authors: Buishand T.A.
Published: April 2008

Climatology is an area with many applications of extreme–value theory. In applications to climatic data it is necessary to consider the distribution ol extremes for dependent random variables and to make allowance for non–stationarity (seasonal variation). It is shown that also for such data the classical limiting distributions for normalized maxima of independent and identically distributed random variables remain useful candidates to describe the distribution of the largest value in a year.

Parameter estimation of extreme–value distributions is briefly reviewed. Attention is paid to variance–reduction of quantile estimates by making use of more observations than just the annual maxima. Three examples of applications deal with topics like the estimation of large quantiles by combining information from several records in a region, shifts in the distribution of maxima due to changes in measurement practices, and the use of covariates.
Simulated annealing: An introduction
Authors: Aarts E.H.L. , van Laarhoven P.J.M.
Published: April 2008

Simulated annealing is a general approach for approximately solving large combinatorial optimization problems. The algorithm is based on an intriguing combination of ideas from at first sight completely unrelated fields of science, viz. combinatorial optimization and statistical physics. On the one hand the algorithm can be viewed as an analogue of an algorithm used in statistical physics for computer simulation of the annealing of a solid to its minimum–energy state, on the other hand it can be considered as a generalization of the well–known iterative improvement approach to combinatorial optimization problems.

In this introductory paper we give a mathematical description of the simulated annealing algorithm and discuss its behaviour from both a theoretical and a practical point of view. The latter is illustrated by applying the algorithm to the travelling salesman problem.

This paper was written to familiarize the readers of Statistica Neerlandica with simulated annealing. It is a summary of papers written earlier by the authors and does not contain any new material.
On the waiting time distribution in a GI/G/1 queue with a Coxian–2 service time distribution
Authors: van Ommeren J.C.W. , Nobel R.D.
Published: April 2008

The purpose of this paper is to derive in an alternative way the result that the complementary waiting–time distribution function in the Gl/G/I queue is the sum of two exponential functions when the service time has a Coxian–2 distribution. The idea is to interpret this type of service–time distribution as the sum of a stochastic number of exponentially distributed phases. In this way the model can be seen as a special G/x/W/1 batch–arrival queue where the batch–size distribution is deduced from the Coxian service–time distribution. For the latter model we give an embedded Markov–chain approach. Because of the special form of the batch–size distribution the steady–state distribution of this Markov chain can be represented as the sum of two geometric terms of which the coefficients can be explicitly given. From this result the waiting–time distribution can be deduced immediately. Apart from its didactic interest the result can be useful to obtain simple approximations for more general GI/G/1 models.
Scheduling identical jobs on uniform parallel machines
Authors: Dessouky M.I. , Lageweg B.J. , Lenstra J.K. , van de Velde S.L.
Published: April 2008

We address the problem of scheduling n identical jobs on m uniform parallel machines to optimize scheduling criteria that are nondecreasing in the job completion times. It is well known that this can be formulated as a linear assignment problem, and subsequently solved in O(n3) time. We give a more concise formulation for minsum criteria, and show that general minmax criteria can be minimized in O(n2) time. We present faster algorithms, requiring only O(n+mlog m) time for minimizing makespan and total completion time, O(nlogn) time for minimizing total weighted completion time, maximum lateness, total tardiness and the weighted number of tardy jobs, and O(nlog2n) time for maximum weighted tardiness. In the case of release dates, we propose an O(nlogn) algorithm for minimizing makespan, and an O(mn2m+1) time dynamic programming algorithm for minimizing total completion time.
An analytical theory of multi‐echelon production/distribution systems
Authors: Langenhoff L.J.G. , Zijm W.H.M.
Published: April 2008

In this paper, we study inventory control problems arising in multi‐echelon production/distribution chains. In these chains, material is delivered by outside suppliers, proceeds through a number of manufacturing stages, and is distributed finally among a number of local warehouses in order to meet market demand. Each stage requires a fixed leadtime; furthermore, we assume a stochastic, stationary end‐item demand process.

The problem to balance inventory levels and service degrees can be modelled and analyzed by defining appropriate cost functions. Under an average cost criterion, we study the three most important structures arising in multi‐echelon systems: assembly systems, serial systems and distribution systems. For all three systems, it is possible to prove exact decomposition results which reduce complex multi‐dimensional control problems to simple one‐dimensional problems. In addition, we establish the optimality of base‐stock control policies.
Comparisons of Bayesian estimation procedures for two‐way contingency tables without interaction
Authors: Jansen M.G.H. , Snijders T.A.B.
Published: April 2008

Bayesian and empirical Bayesian estimation methods are reviewed and proposed for the row and column parameters in two‐way Contingency tables without interaction. Rasch's multiplicative Poisson model for misreadings is discussed in an example. The case is treated where assumptions of exchangeability are reasonablea priorifor the unknown parameters. Two different types of prior distributions are compared, It appears that gamma priors yield more tractable results than lognormal priors.
Identification with latent variables
Authors: Wegge L.L.
Published: April 2008

This is an essay on a unified approach to the identifiability problem in static models with and without hidden endogenous variables. As is well known, when some of these variables are unobserved, the prior information requirements for models when all endogenous variables are observed, are still there. In addition, extra prior information that takes the place of the means and covariances of the missing variables will have to be supplied directly or indirectly by the statistical researcher. In the paper we characterize the quality and quantity of the required information for the general linear static model and apply it when the model is i) an econometric demand and supply model with missing observations on the quantity transacted, ii) a factor analysis model with observed characteristics of the test takers and iii) a LISREL Model without fixed exogenous variables. With unknown true parameters, the exact rank conditions are seldom verifiable but we do recommend an implementable check‐list that is adequate for almost all parameters.
Models with latent variables: LISREL versus PLS
Authors: Schneeweiss H.
Published: April 2008

Summary: LISREL and PLS are two different ways of modelling latent variables and their relations to each other within a set of manifest variables. These two models are contrasted with each other. In the special case of two groups of manifest variables the relations that exist between corresponding parameters and latent variables of both types of models are revealed.
A comparison of several approximations to the power function of the likelihood ratio test in covariance structure analysis*
Authors: Satorra A. , Saris W.E. , de Pijper W.M.
Published: April 2008

In this paper we compare alternative asymptotic approximations to the power of the likelihood ratio test used in covariance structure analysis for testing the fit of a model. Alternative expressions for the noncentrality parameter (ncp) lead to different approximations to the power function. It appears that for alternative covariance matrices close to the null hypothesis, the alternative ncp's lead to similar values, while for alternative covariance matrices far from Hothe different expressions for the ncp can conflict substantively. Monte Carlo evidence shows that the ncp proposed in Satorra and Saris (1985) gives the most accurate power approximations.
Linear rank tests for comparing treatments with a control when data are subject to unequal patterns of censorship
Authors: Chakraborti S. , Desu M.M.
Published: April 2008

A class of asymptotically distribution‐free tests is considered for comparing several treatments with a control when the, data are subject to unequal right‐censorship. A particular member of this class is proposed for use in practice and an illustrative numerical example is given. A general result for the Pitman efficacy of a test based on an asymptotically normal test statistic is proved for the multiparameter case and using this result the efficacy of the proposed class of tests is obtained under sequences of translation and proportional hazards alternatives. Simulation studies are conducted to compare the performance of the proposed test, in terms of power, with some other tests.
On identification disclosure and prediction disclosure for microdata
Authors: Skinner C.J.
Published: April 2008

Two definitions of statistical disclosure ‐ identification disclosure and prediction disclosure ‐ are compared. Identification disclosure implies prediction disclosure but not vice versa. It is argued, however, that if sampling takes place then cases where prediction disclosure occurs and identification disclosure does not either have very small probability or do not present disclosure problems different from those normally met in the release of aggregate statistics. Finally the estimation of population uniqueness using the Poisson‐Gamma model is considered.
Strategies for measuring risk in public use microdata files
Authors: Greenberg B.V. , Zayatz L.V.
Published: April 2008

Statistical agencies have the responsibility to design data release strategies which will not violate pledges of nondisclosure either through intent or neglect. In addition to ethical and legal concerns, statistical offices must be mindful that violating pledges of confidentiality may undermine an agency's ability to collect data due to loss of public trust. Statistical organizations also have the obligation to make information available to a variety of individuals and institutions to allow for informed discussion from differing perspectives on a range of issues. However, it is through fine, accurate detail on a file that risks of disclosure arise. In this report we discuss strategies for controlling risk in the release of public use microdata files. The equivalence class structure of a microdata file is defined and we show how the classic entropy function can be employed on the equivalence class structure to provide a measure of relative risk.
Disclosure risks for microdata
Authors: Mokken R.J. , Kooiman P. , Pannekoek J. , Willenborg L.C.R.J.
Published: April 2008

In this paper a model is developed for assesing disclosure risks of a microdata set. It is an extension of the one presented in Bethlehem et al. (1988). It is used to calculate (an upper bound of) the risk that an investigator is able to reidentify at least one individual in an anonimyzed data set, and hence discloses some sensitive information about him. This risk is shown to depend on, among other things, two variables which can be controlled by the statistical office which is disseminating such a data set: the ‘coarseness’ of the key variables and the size of the data set. The model yields guidelines as to the usage of these two instruments to control the disclosure risk.
In memoriam Albert Verbeek (1946–1990)
Authors: Kroonenberg P.M.
Published: April 2008

This In memoriam is divided into three parts. The first part is a tribute to Albert Verbeek as a person and a scientist. In the second part, a short note is reproduced, translated from the Dutch, as an example how he applied himself to all kinds of problems. The final part consists of an overview of his major publications.
Robust dynamic clustering
Authors: Aboukalam M.A.F. , AI‐Nachawati H.
Published: April 2008

The dynamic clustering (DC) algorithm is a method for discovering clusters in a given population. Unfortunately the classical DC algorithms fail to perform well in the presence of outliers. A robust dynamic clustering (RDC) algorithm is introduced to overcome this problem. Robust estimates of the location vector and the covariance matrix are calculated in the affine invariant case. A simulation study is presented to demonstrate the basic difference between the DC and the RDC algorithms. Three kinds of optimization criteria are used in case of contaminated multivariate normal distributions.
Robustness of some non‐uniform random variate generators
Authors: Deng L.Y. , Chhikara R.S.
Published: April 2008

Often the usefulness of a random variate generator for a distribution is based on the successful generation of independent variates from the uniform distribution. However, no pseudo‐random number generator is capable of generating a truly random uniform sequence. As the cost of computations is now dramatically reduced, the computational efficiency should not be the primary criterion in choosing a good generator. Proposed here is a robustness criterion which is designed to study the effect of an imperfect pseudo‐random number generator on the accuracy of a random variate generator. In particular, the beta and binomial variate generators are examined for their robustness to the non‐uniformity of a pseudo‐random number generator.
A characterization of gamma mixtures of stable laws motivated by limit theorems
Authors: Pakes A.G.
Published: April 2008

This pape; is concerned with distributional solutions of X1+…+ Xmd= U(X1+…+ Xm+n) where the X's are iid and independent of U which takes values in [0,1]. When U is a constant the only possible non‐trivial solutions lie in the class of semi‐stable laws, and they are stable under a simple regularity condition. This material is reviewed. A unified account is given of some results known for the case where U has a beta (α, 1) law, apparently the only other case allowing explicit identification of all possible solutions.
A note on mixed Poisson approximation
Authors: Majsnerowska M.
Published: April 2008

Conditions sufficient for the weak convergence of sums of 0–1 random variables indexed byk‐sets to a mixed Poisson law are presented. An example of applications concerning “distance” random variables is also provided.
Computation of robust estimates of multivariate location and shape
Authors: Rocke D. M. , Woodruff D. L.
Published: April 2008

This paper reviews the state of the art in the computation of robust estimates of multivariate location and shape using combinatorial estimators such as the minimum volume ellipsoid (MVE) and iterative M‐ and S‐estimators. We also present new results on the behavior of M‐ and S‐estimators in the presence of different types of outliers, and give the first computational evidence on compound estimators that use the MVE as a starting point for an S‐estimator. Problems with too many data points in too many dimensions cannot be handled by any available technology; however, the methods presented in this paper substantially extend the size of problem that can be successfully handled.
Estimation in a growth study with irregular measurement times
Authors: Poortema K. , Tarnminga R. Y. J. , Schaafsma W.
Published: April 2008

Between 1982 and 1988 a growth study was carried out at the Division of Pediatric Oncology of the University Hospital of Groningen. A special feature of the project was that sample sizes are small and that ages at entry may be very different. In addition the intended design was not fully complied with. This paper highlights some aspects of the statistical analysis which is based on (1) reference scores, (2) statistical procedures allowing for an irregular pattern of measurement times caused by missing data and shifted measurement times.
The simultaneous processes of ageing and mortality
Authors: Mulder P. G. H.
Published: April 2008

When studying the stochastic process of mortality related to observed co‐variables in a cohort of subjects followed in time, it is usually assumed that the observed covariables are given, non‐stochastic quantities. In this way one can predict only a subject's survivor function, given certain values of the covariables at baseline. Continuous covariables are assumed to have (approximately) a multivariate Gaussian distribution in a cohort and to evolve with random fluctuation in subjects as a consequence of ageing. Woodbury et al. elaborated a model where this evolution‐diffusion process (called ageing process) can be incorporated and kept in balance by an appropriately modelled mortality selection process, so that the distribution of the covariables in the cohort remains (approximately) Gaussian. The analytical tractability of this model allows one to readily calculate the cohort survivor function as ultimately being epidemiologically more relevant than individual survivorship.
A simple approach for the analysis of generalizea linear mixed models
Authors: Engel B. , Keen A.
Published: April 2008

A broad class of generalized linear mixed models, e.g. variance components models for binary data, percentages or count data, will be introduced by incorporating additional random effects into the linear predictor of a generalized linear model structure. Parameters are estimated by a combination of quasi‐likelihood and iterated MINQUE (minimum norm quadratic unbiased estimation), the latter being numerically equivalent to REML (restricted, or residual, maximum likelihood). First, conditional upon the additional random effects, observations on a working variable and weights are derived by quasi‐likelihood, using iteratively re‐weighted least squares. Second, a linear mixed model is fitted to the working variable, employing the weights for the residual error terms, by iterated MINQUE. The latter may be regarded as a least squares procedure applied to squared and product terms of error contrasts derived from the working variable. No full distributional assumptions are needed for estimation. The model may be fitted with standardly available software for weighted regression and REML.
Covariance formulas via marginal martingales
Authors: Wellner J. A.
Published: April 2008

Prenctice and Cai recently introduced and studied the function C defined as the covariance function of the two marginal counting process martingales of a pair of dependent survival times (T1, T2). They show that the function C together with the marginal distributions determines the joint survival function F of (T1, T2). In this note we show how the key characterizing equation of Prentice and Cai yields a formula for the covariance of T1 and T2 in termsof the marginal mean residual life functions and C. The resulting formula generalizes a formula for the variance of a one‐dimensional random variable Tdueto Pyke (1965). We also explore several generalizations of the covariance formula, and obtain a valid k‐dimensional version of the Prentice and Cai formula.
Some properties of the length of the shortest half
Authors: Christmann A. , Gather U. , Scholz G.
Published: April 2008

This paper discusses some properties of the length of the shortest half proposed by Rousseeuw and Leroy (1988) as a robust scale estimator.