bluuebunny/crossref_metadata_2025 huggingface dataset:
A Perspective on the Accuracy of Economic Observations
Authors: Kenessey Zoltan
Published: May 2007

In 1950 appeared the first edition of Oskar Morgenstern's Famous book, The Accuracy of Economic Observations. Nearly half a century later it is timely to return to Morgenstern's diagnosis and to contemplate his therapeutic recommendations. Morgenstern's vision can and should inform the consideration of the topic today because of the continued validity of many of his findings. His work still provides stimuli for studying the general problems of measurement, the varying requirements for accuracy, the issues of aggregate macroeconomic measures, and the prospects for economic and social measurement. This is so even if some of the bleaker assessments by Morgenstern, notwithstanding their technical merits, provide little or no practical guidance for statistical activities. In this context it is enlightening to recall the different practical attitudes adopted by Keynes and by some of his contemporaries in Germany regarding theoretical difficulties with aggregate macroeconomic data.
A Unified View of Signal Extraction, Benchmarking, Interpolation and Extrapolation of Time Series
Authors: Dagum Estela Bee , Cholette Pierre A. , Chen Zhao‐Guo
Published: May 2007

Time series data are often subject to statistical adjustments needed to increase accuracy, replace missing values and/or facilitate data analysis. The most common adjustments made to original observations are signal extraction (e.g. smoothing), benchmarking, interpolation and extrapolation. In this article, we present a general dynamic stochastic regression model, from which most of these adjustments can be performed, and prove that the resulting generalized least square estimator is minimum variance linear unbiased. We extend current methods to include those cases where the signal follows a mixed model (deterministic and stochastic components) and the errors are autocorrelated and heteroscedastic.
Professional Development for Teachers of probability and Statistics: Into an Era of Technology
Authors: Watson Jane M.
Published: May 2007

The focus of this paper is the professional development of teachers of probability and statistics at school level. Within a world where the statistics curriculum is changing at school level, the professional development needs of teachers of statistics are changing and the technology to meet these needs is changing as well. This paper reviews the work in the field, describes the development of a multimedia package for professional development of statistics teachers and looks to the futrue.
Bayesian Comparison of ARIMA and Stationary ARMA Models
Authors: Marriott John , Newbold Paul
Published: May 2007

Time series analysts have long been concerned with distinguishing stationary “generating processes” from processes for which differencing is required to induce stationarity. In practical applications, this issue is addressed almost invariably through formal hypothesis testing. In this paper, we explore some aspects of the Bayesian approach to the problem, leading to the calculation of posterior odds ratios. Interesting features arise in the simplest possible variant of the problem, where a choice has to be made between a random walk and a stationary first order autoregressive model. We discuss in detail the analysis of this case, and also indicate how our approach extends to the more general comparison of an ARIMA model with a stationary competitor.
Doing Least Squares: Perspectives from Gauss and Yule
Authors: Aldrich John
Published: May 2007

Gauss introduced a procedure for calculating least squares estimates and their precisions. Yule introduced a new system of notation adapted to correlation analysis. This paper describes these formalisms and compares them with the matrix and vector space formalisms used in modern regression analysis.
The Measurement and Analysis of Poverty and Inequality: An Application to Spanish Conurbations
Authors: Bellido N.P. , Jano M.D. , Ortega F.J. López , Martín‐Guzmán M.P. , Toledo M.I.
Published: May 2007

Poverty as a multidimensional phenomenon can be approached from different points of view. In this paper we study poverty in large towns in Spain taking into consideration three different definitions: a) relative monetary poverty, or scarcity of resources as compared with population averages, b) poverty measured through physical indicators, i.e. deprivation of certain goods, and c) subjective poverty. This last one appears to be related to inequality, which is also considered and analyzed. The source of statistical information used is the Spanish Household Budget Survey of 1990–91. Possibilities and drawbacks of this survey in the analysis of poverty and inequality are also reviewed.
Training Employees for African Statistical Offices
Authors: Ching'anda Enock F. , Ntozi James P.M.
Published: May 2007

A review of the organizational set‐up of a national statistical office, its staffing levels and subjects covered has been described. Two groups of employees of a statistical office are considered with respect to the teaching of statistics, namely those already in employment and those expected to be employed by a statistical office. The Statistical Training Programme for Africa (STPA), under which the present study was undertaken, improvement and strengthening of statistical training programmes for employees or expected employees of a statistical office, are described including selected aspects of the programme. Teaching programmes for those currently in employment with the objective of improving their work performance are also described. Achievements and problems of the programme are given. In conclusion a new framework for revitalisation of teaching of statistics in Africa in the 1990s is mentioned.
Design‐based or Prediction‐based Inference? Stratified Random vs Stratified Balanced Sampling
Authors: Brewer K. R. W.
Published: May 2007

Early survey statisticians faced a puzzling choice between randomized sampling and purposive selection but, by the early 1950s, Neyman's design‐based or randomization approach had become generally accepted as standard. It remained virtually unchallenged until the early 1970s, when Royall and his co‐authors produced an alternative approach based on statistical modelling. This revived the old idea of purposive selection, under the new name of “balanced sampling”. Suppose that the sampling strategy to be used for a particular survey is required to involve both a stratified sampling design and the classical ratio estimator, but that, within each stratum, a choice is allowed between simple random sampling and simple balanced sampling; then which should the survey statistician choose? The balanced sampling strategy appears preferable in terms of robustness and efficiency, but the randomized design has certain countervailing advantages. These include the simplicity of the selection process and an established public acceptance that randomization is “fair”. It transpires that nearly all the advantages of both schemes can be secured if simple random samples are selected within each stratum and a generalized regression estimator is used instead of the classical ratio estimator.
Social Change: Measurement and Theory*
Authors: Garonna Paolo , Triacca Umberto
Published: May 2007

Societal change, which takes a variety of directions and forms and in no way can be assimilated or reduced to a single dimension, is often accompanied by a perception of insufficient understanding and lack of control. There is a frustrated need for mastering complexity and instability, separating the voluntary from the involuntary, the intended from the unintended, opportunities from risks, getting to the real causes and dominating the uncertain implications of social change. Social change catches us unprepared and confused.

In this context statistics are generally considered a fundamental instrument of knowledge, but also part of the problem! In the public debate and in the specialized literature, the ability to measure social phenomena through current statistics and indicators is increasingly questioned. Data‐it is claimed‐are lacking, particularly longitudinal data; their quality (accuracy, relevance, timeliness, comparability, etc.) should be improved; indicators do not provide early warning signals, policy performance evaluation, and a precise indication of outcomes. Statistics cannot be used as a reliable and timely basis for decision making by individuals, organizations, governments, and for understanding these decisions. In some cases, statistics have been accused of giving a misleading and false picture of reality: do we measure the real extent of social exclusion and unemployment? Do we fully capture the quality of life and the degradation of the environment? Mismeasurement has been deemed by some commentators as being responsible for the wrong focus in inflation and stabilization policies, science and technology, unemployment and poverty. The productivity paradox, the informal economy, failure to measure welfare and the quality of urban life are instances where statistics do not seem to provide complete and satisfactory answers to the demand for information and knowledge. Our paper illustrates how, quite independently of measurement techniques and data production processes, the inadequacy of the conceptual framework may explain mismeasurement in relation to complex (multidimensional) and dynamic social phenomena. It is then to social theories, explanations and interpretations that statisticians need to turn, in order to come to grips with the new challenges in social measurement.

We will develop this thesis looking at a few cases where measurement issues can be connected to both theoretical and empirical difficulties. The statistical gap which reveals itself in the mismeasurement or difficult measurement of social phenomena is closely interconnected with the social science gap. Only close collaboration between statisticians and social scientists can bring about continuous advancement in social science and quality improvement in social statistics.
Statistical Integration Through Metadata Management
Authors: Colledge Michael J.
Published: May 2007

Faster and more versatile technology is fuelling user demand for statistical agencies to produce an ever wider range of outputs, and to ensure those outputs are consistent and mutually related to the greatest extent possible. Statistical integration is an approach for enhancing the information content of separate statistical collections conducted by an agency, and is necessary for consistency. It has two aspects‐conceptual and physical‐the former being a prerequisite for the latter. This paper focuses on methods for achieving statistical integration through better management of metadata. It draws on experiences at the Australian Bureau of Statistics in the development and use of a central repository (the “Information Warehouse”) to manage data and metadata. It also makes reference to comparable initiatives at other national statistical agencies.

The main conclusions are as follows. First, a prototyping approach is required in developing new functionality to support statistical integration as it is not clear in advance what tools are needed. Second, metadata from separate collections cannot easily be rationalised until they have been loaded to a central repository and are visible alongside one another so their inconsistencies are evident. Third, to be effective, conceptual integration must be accompanied by physical integration. Fourth, there is great scope for partnerships and exchange of ideas between agencies. Finally, statistical integration must be built into the ongoing collection processes and viewed as a way of life.
Evolution of International Statistical Standards via Life Cycle of Products and Services
Authors: Boulanger Michèle , Johnson Mark , Perruchet Christophe , Thyregod Poul
Published: May 2007

This paper describes international statistical standards in the context of the product life cycle. To set the stage, the historical evolution of standardization is traced from the Xia Dynasty of China to the present. The transition from local standards geared for manufacturing to national and then international standards is highlighted with acceptance sampling standards. International statistical standards now cover a broad range of topics beyond acceptance sampling, so a scheme is needed to organize them into a coherent structure. The product Life cycle provides just such a framework. The product Life cycle (which is subsumed to include service, as well) is partitioned into four main “megaphases”, namely: conception, development, delivery and maturity and death. Each megaphase is linked to relevant statistical methods in general and statistical standards in particular. A gap analysis identifies potential future directions of statistical standards developments and the attendant role that statisticians can continue to play in this arena.
Semi‐ and Non‐parametric Bayesian Analysis of Duration Models with Dirichlet Priors: A Survey
Authors: Florens J.‐P. , Mouchart M. , Rolin J.‐M.
Published: May 2007

The object of this paper is to review the main results obtained in semi‐ and non‐parametric Bayesian analysis of duration models. Standard nonparametric Bayesian models for independent and identically distributed observations are reviewed in line with Ferguson's pioneering papers. Recent results on the characterization of Dirichlet processes and on nonparametric treatment of censoring and of heterogeneity in the context of mixtures of Dirichlet processes are also discussed. The final section considers a Bayesian semiparametric version of the proportional hazards model.
Measurement Biases in Consumer Price Indexes
Authors: White Alan G.
Published: May 2007

The Consumer Price Index (CPI) measures the cost of purchasing a fixed basket of goods at a fixed sample of outlets over time, and can be thought of as a practical approximation to a “true” cost‐of‐living index, and a measure of general inflation for the economy. In more recent times, concerns over the possibility that the U.S. CPI overstates the rate of inflation have grown. Annual changes in the CPI are used to adjust social security benefits, and wage contracts are often indexed to CPI changes. To the extent that the CPI overstates the rate of inflation individuals are being compensated for changes in the cost‐of‐living that have not occurred–with enormous implications for government fiscal budgets. This paper presents an up‐to‐date survey of the principal sources of measurement error or bias in the CPI. A number of sources of bias are examined, including the commodity substitution bias, the outlet substitution bias, and the elementary index bias. Traditional bilateral index number theory assumes that the number of goods remains constant over the pricing period and furthermore, that the goods are of unchanging quality. Changes in either of these give rise to two further biases: the new goods bias and the quality bias.
De Vetula: a Medieval Manuscript Containing Probability Calculations
Authors: Bellhouse D.R.
Published: May 2007

De Vetula, a poem that contains probability calculations on the throw of three dice, was written in the mid‐thirteenth century. The poem was widely circulated, read and quoted. There is strong evidence that some of the medieval readers clearly understood how the probability calculations were obtained. Based on the discussion given here, it is put forward that an elementary probability calculus was established and known in Europe from about the year 1250. A translation of the relevant section of the poem is given.
Fisher's “Inverse Probability” of 1930
Authors: Aldrich John
Published: May 2007

In 1930 R. A. Fisher put forward the fiducial argument. This paper discusses the argument and its origins in Fisher's earlier work. It also emphasises the contribution of Mordecal Ezekiel to the 1930 publication.
Measurement and its Uses: Harmonization and Quality in Social Statistics
Authors: Desrosières Alain
Published: May 2007

The European construction has induced a strong demand of harmonization of statistics of the various countries. The latter can be focused on an harmonization of outputs, already practised for a long time by national accountants: the statistical variables are defined in common, then each country measures them according to its own means. On the other hand, the harmonization of inputs, more ambitious, seeks a standardization of all the construction process and data collection. This leads to distinguish clearly the two moments of use and of production of economic and social statistics. Now the same distinction is made in the debates over the notion of quality of statistics, which contrast the quality of the product with the one of the process. This quality cannot be judged independently from the expected uses of these statistics and of their form of social credibility. From this point of view, the various harmonization levels are compared with the various forms of connection and convertibility between the national currencies.
The Role of Behavioral Survey Methodologists in National Statistical
Authors: Dillman Don A.
Published: May 2007

The expertise of behavioral survey methodologists is needed in national statistical agencies because of the necessity of using theory and research from the social sciences to reduce survey error. In this paper various social science based explanations for measurement error and nonresponse error are described in order to illustrate the conceptual foundations of such error reduction efforts. Three roles for behavioral survey methodologists in national statistical agencies are then discussed. They include: 1) bring an error reduction perspective to bear in an influential way for all aspects of designing and implementing agency surveys; 2) bring theoretical efficiency and effectiveness to experimental tests of alternative questionnaire designs and implementation procedures through the use of theories, concepts and pretests and findings of past behavioral science research; and 3) contribute to the expanding science of survey methodology.
Robust Methods for the Analysis of Income Distribution, Inequality and Poverty
Authors: Victoria‐Feser Maria‐Pia
Published: May 2007

Income distribution embeds a large field of research subjects in economics. It is important to study how incomes are distributed among the members of a population in order for example to determine tax policies for redistribution to decrease inequality, or to implement social policies to reduce poverty. The available data come mostly from surveys (and not censuses as it is often believed) and often subject to long debates about their reliability because the sources of errors are numerous. Moreover the forms in which the data are availabe is not always as one would expect, i.e. complete and continuous (microdata) but one also can only have data in a grouped form (in income classes) and/or truncated data where a portion of the original data has been omitted from the sample or simply not recorded.

Because of these data features, it is important to complement classical statistical procedures with robust ones. In tis paper such methods are presented, especially for model selection, model fitting with several types of data, inequality and poverty analysis and ordering tools. The approach is based on theInfluence Function (IF)developed by Hampel (1974) and further developed by Hampel, Ronchetti, Rousseeuw & Stahel (1986). It is also shown through the analysis of real UK and Tunisian data, that robust techniques can give another picture of income distribution, inequality or poverty when compared to classical ones.
Women in the Statistics Profession: A Status Report
Authors: Carlson Beverley A.
Published: May 2007

The mandate of the International Statistical Institute (ISI) is to foster international statistical work and interchange among statisticians and countries. However, women are under‐represented in the ISI and this situation is a cause for concern in the Institute and its membership and particularly the ISI Committee on Women in Statistics (CWS). This paper analyses the representation of women in the ISI and in the statistics profession which is low in virtually every country, a pattern of generations. It looks at the diverse realities among countries and regions, and the broader context of women working in the scientific professions.
A Review of Statistical Methods for Genome Mapping
Authors: Jones Hywel B.
Published: May 2007

Framework maps of the human genome are an important staging post in the on‐going effort to sequence the entire genome. The existence of high quality maps is also a prerequistite for studies attempting to determine the location of genes involved in common diseases. The basic experimental approaches to constructing both genetic and physical maps are briefly described as well as their respective uses. A variety of statistical approaches to map construction are outlined including parsimony, maximum likelihood and Bayesian methodologies. The mostly widely used of these, the method of maximum likelihood, is discussed in detail, particularly in the context of physical mapping using radiation hybrids. Finally, current statistical issues and problems in the field of genome mapping are described.
Linkage Disequilibrium Mapping of Disease Susceptibility Genes in Human Populations
Authors: Clayton David
Published: May 2007

The paper reviews recent work on statistical methods for using linkage disequilibrium to locate disease susceptibility genes, given a set of marker genes at known positions in the genome. The paper starts by considering a simple deterministic model for linkage disequilibrium and discusses recent attempts to elaborate it to include the effects of stochastic influences, of “drift”, by the use of either Writht‐Fisher models or by approaches based on the coalescence of the genealogy of the sample of disease chromosomes. Most of this first part of the paper concerns a series of diallelic markers and, in this case, the models so far proposed are hierarchical probability models for multivariate binary data. Likelihoods are intractable and most approaches to linkage disequilibrium mapping amount to marginal models for pairwise associations between individual markers and the disease susceptibility locus. Approaches to evalutation of a full likelihood require Monte Carlo methods in order to integrate over the large number of unknowns. The fact that the initial state of the stochastic process which has led to present‐day allele frequencies is unknown is noted and its implications for the hierarchical probability model is discussed. Difficulties and opportunities arising as a result of more polymorphic markers and extended marker haplotypes are indicated. Connections between the hierarchical modelling approach and methods based upon identity by descent and haplotype sharing by seemingly unrelated case are explored. Finally problems resulting from unknown modes of inheritance, incomplete penetrance, and “phenocopies” are briefly reviewed.
MCMC Estimation of Multi‐locus Genome Sharing and Multipoint Gene Location Scores
Authors: Thompson E. A.
Published: May 2007

Effective linkage detection and gene mapping requires analysis of data jointly on members of extended pedigrees, jointly at multiple genetic markers. Exact likelihood computation is then often infeasible, but Markov chain Monte Carlo (MCMC) methods permit estimation of posterior probabilities of genome sharing among relatives, conditional upon marker data. In principle, MCMC also permits estimation of linkage analysis location score curves, but in practice effective MCMC samplers are hard to find. Although the whole‐meiosis Gibbs sampler (M‐sampler) performs well in some cases, for extended pedigrees and tightly linked markers better samplers are needed. However, using the M‐sampler as a proposal distribution in a Metropolis‐Hastings algorithm does allow genetic interference to be incorporated into the analysis.
On the Application of Markov Chain Monte Carlo Methods to Genetic Analyses on Complex Pedigrees
Authors: Sheehan N. A.
Published: May 2007

Markov chain Monte Carlo methods are frequently used in the analyses of genetic data on pedigrees for the estimation of probabilities and likelihoods which cannot be calculated by existing exact methods. In the case of discrete data, the underlying Markov chain may be reducible and care must be taken to ensure that reliable estimates are obtained. Potential reducibility thus has implications for the analysis of the mixed inheritance model, for example, where genetic variation is assumed to be due to one single locus of large effect and many loci each with a small effect. Similarly, reducibility arises in the detection of quantitative trait loci from incomplete discrete marker data. This paper aims to describe the estimation problem in terms of simple discrete genetic models and the single‐site Gibbs sampler. Reducibility of the Gibbs sampler is discussed and some current methods for circumventing the problem outlined.
Schwarz, Wallace, and Rissanen: Intertwining Themes in Theories of Model Selection
Authors: Lanterman Aaron D.
Published: May 2007

Investigators interested in model order estimation have tended to divide themselves into widely separated camps; this survey of the contributions of Schwarz, Wallace, Rissanen, and their coworkers attempts to build bridges between the various viewpoints, illuminating connections which may have previously gone unnoticed and clarifying misconceptions which seem to have propagated in the applied literature. Our tour begins with Schwarz's approximation of Bayesian integrals via Laplace's method. We then introduce the concepts underlying Rissanen's minimum description length principle via a Bayesian scenario with a known prior; this provides the groundwork for understanding his more complex non‐Bayesian MDL which employs a “universal” encoding of the integers. Rissanen's method of parameter truncation is contrasted with that employed in various versions of Wallace's minimum message length criteria. Rissanen's more recent notion of stochastic complexity is outlined in terms of Bernardo's information‐theoretic derivation of the Jeffreys prior.
Probabilistic Models for Bacterial Taxonomy
Authors: Gyllenberg M. , Koski T.
Published: May 2007

We give a survey of different partitioning methods that have been applied to bacterial taxonomy. We introduce a theoretical framework, which makes it possible to treat the various models in a unified way. The key concepts of our approach are prediction and storing of microbiological information in a Bayesian forecasting setting. We show that there is a close connection between classification and probabilistic identification and that, in fact, our approach ties these two concepts together in a coherent way.
Ethnic, Religious and Language Groups: Towards a Set of Rules for Data Collection and Statistical Analysis
Authors: Haug Werner
Published: May 2007

The establishment of reliable and authoritative figures on ethnic, religious and language groups plays a prominent role in efforts to fight discrimination and foster individual human rights as well as minority rights. But how is an ethnic or religious group defined? Who belongs to it? How can we measure its characteristics? There is no consensus concerning these questions among statisticians, demographers and the social sciences at large. The article builds on the rich experience of Europe, including the multinational empires of the past. It identifies the background of diverging concepts and definitions, different data sources and measurement problems of ethnic, religious and language groups. The conclusion presents a set of rules and guidelines for the improvement of data collection, especially in the context population censuses and sample surveys, as well as for data analysis.
Meaningful Measures: Indicators on Progress, Progress on Indicators
Authors: de Vries Willem F.M.
Published: May 2007

This article reviews the international debate on statistical indicators. It describes historical backgrounds, as well as the present chaotic situation. It discusses what statistical indicators are and what they are for, as well as criteria for the choice of indicators, designed to monitor the achievement of economic, social, demographic, environmental and other goals set by United Nations conferences. Some suggestions for future work are made.
Uses, Abuses and Misuses of Significance Tests in the Scientific Community: Won't the Bayesian Choice be Unavoidable?
Authors: Lecoutre Bruno , Lecoutre Marie‐Paule , Poitevineau Jacques
Published: May 2007

The current context of the “significance test controversy” is first briefly discussed. Then experimental studies about the use of null hypothesis significance tests by scientific researchers and applied statisticians are presented. The misuses of these tests are reconsidered as judgmental adjustments revealing researchers’requirements towards statistical inference. Lastly alternative methods are considered. Consequently we automatically ask ourselves “won't the Bayesian choice be unavoidable?”
On Conformity Testing and the Use of two Stage Procedures
Authors: Holst Erik , Thyregod Poul , Wilrich Peter‐Th.
Published: May 2007

Conformity testing is a systematic examination of the extent to which an entity conforms to specified requirements. Such testing is performed in industry as well as in regulatory agencies in a variety of fields. In this paper we discuss conformity testing under measurement or sampling uncertainty. Although the situation has many analogies to statistical testing of a hypothesis concerning the unknown value of the measurand there are no generally accepted rules for handling measurement uncertainty when testing for conformity.

Usually the objective of a test for conformity is to provide assurance of conformity. We therefore suggest that an appropriate statistical test for conformity should be devised such that there is only a small probability of declaring conformity when in fact the entity does not conform. An operational way of formulating this principle is to require that whenever an entity has been declared to be conforming, it should not be possible to alter that declaration, even if the entity was investigated with better (more precise) measuring instruments, or measurement procedures.

Some industries and agencies designate specification limits under consideration of the measurement uncertainty. This practice is not invariant under changes of measurement procedure. We therefore suggest that conformity testing should be based upon a comparison of a confidence interval for the value of the measurand with some limiting values that have been designated without regard to the measurement uncertainty. Such a procedure is in line with the recently established practice of reporting measurement uncertainty as “an interval of values that could reasonably be attributed to the measurand”.

The price to be paid for a reliable assurance of conformity is a relatively large risk that the procedure will fail to establish conformity for entities that only marginally conform. We suggest a two‐stage procedure that may improve this situation and provide a better discriminatory ability. In an example we illustrate the determination of the power function of such a two‐stage procedure.
The History of the Dirichlet and Liouville Distributions
Authors: Gupta Rameshwar D. , Richards Donald St. P.
Published: May 2007

The Dirichlet distributions have long been the subject of intense scrutiny in statistics and probability. Despite the enormous interest in, and wide‐ranging applications of, these distributions, little appears to be known about their history. In this article we review the development of the Dirichlet distributions and their companions, the Liouville distributions. After reviewing some integral formulas of Dirichlet and Liouville, we survey the theory and applications of these distributions in statistics.
Estimation Methods and Related Systems at Statistics Canada
Authors: Singh M.P , Hidiroglou M.A. , Gambino J.G. , Kovaçević M.S.
Published: May 2007

This paper provides an overview of research in estimation techniques, their application, and the development of generalized estimation systems at Statistics Canada. In Canada, the demand for more detailed and better quality cross‐sectional data related to various sodo‐economic issues has increased significantly in recent years. Also, there has been increasing interest in longitudinal data to better understand and interpret the relationships among variables, necessitating the implementation of a number of large scale panel surveys by Statistics Canada. The paper briefly discusses estimation for longitudinal data and a weighting approach developed for cross‐sectional data Prom these surveys. For cross‐sectional household and business surveys, as well as the census of population, appropriate dibration estimators developed for each situation are briefly discussed. In addition, regression composite estimation, a method developed to improve the quality of cross‐sectional estimates from rotating panel surveys such as the Canadian Labour Force Survey, is presented. With regard to more detailed cross‐sectional estimates at sub‐provincial levels, different approaches to small area estimation developed for various programs are also presented. We SUmmarize the various modules developed lor the GeneraIiized Ektimation System. important new developments within the system include two‐phase estimation as well as the estimation of variance for a number of imputation procedures. We briefly review the status of current estimation research on selected topics as well as the direction of future research.
Sampling and Estimation Issues for Annual and Sub‐annual Canadian Business Surveys
Authors: Hidiroglou Michael A. , Laniel Normand
Published: May 2007

A typical Business Register (BR) is mainly based on administrative data files provided by organisations that produce them as a by‐product of their function. Such files do not necessarily yield a perfect Business Register. A good BR should have the following characteristics: (1) It should reflect the complex structures of businesses with multiple activities, in multiple locations or with multiple legal entities; (2) It should be free of duplication, extraneous or missing units; (3) It should be properly classified in terms of key stratification variables, including size, geography and industry; (4) It should be easily updateable to represent the “newer” business picture, and not lag too much behind it. In reality, not all these desirable features are fully satisfied, resulting in a universe that has missing units, inaccurate structures, as well as improper contact information, to name a few defects.

These defects can be compensated by using sampling and estimation procedures. For example, coverage can be improved using multiple frame techniques, and the sample size can be increased to account for misclassification of units and deaths on the register. At the time of estimation, auxiliary information can be used in a variety of ways. It can be used to impute missing variables, to treat outliers, or to create synthetic variables obtained via modelling. Furthermore, time lags between the birth of units and the time that they are included on the register can be accounted for appropriately inflating the design‐based estimates.
Data Science: an Action Plan for Expanding the Technical Areas of the Field of Statistics
Authors: Cleveland William S.
Published: May 2007

An action plan to enlarge the technical areas of statistics focuses on the data analyst. The plan sets out six technical areas of work for a university department, and advocates a specific allocation of resources devoted to research in each area and to courses in each area. The value of technical work is judged by the extent to which it benefits the data analyst, either directly or indirectly. The plan is also applicable to government research labs and corporate research organizations.
A Tutorial on Reversible Jump MCMC with a View toward Applications in QTL‐mapping
Authors: Waagepetersen Rasmus , Sorensen Daniel
Published: May 2007

A tutorial derivation of the reversible jump Markov chain Monte Carlo (MCMC) algorithm is given. Various examples illustrate how reversible jump MCMC is a general framework for Metropolis‐Hastings algorithms where the proposal and the target distribution may have densities on spaces of varying dimension. It is finally discussed how reversible jump MCMC can be applied in genetics to compute the posterior distribution of the number, locations, effects, and genotypes of putative quantitative trait loci.
A Simulation Approach to Nonparametric Empirical Bayes Analysis
Authors: Dellaportas Petros , Karlis Dimitris
Published: May 2007

We deal with general mixture of hierarchical models of the formm(x) = føf(x |θ) g (θ)dθ, whereg(θ)andm(x)are called mixing and mixed or compound densities respectively, and θ is called the mixing parameter. The usual statistical application of these models emerges when we have dataxi, i = 1,…,nwith densitiesf(xi|θi)for given θi, and the θ1are independent with common densityg(θ). For a certain well known class of densitiesf(x |θ), we present a sample‐based approach to reconstructg(θ). We first provide theoretical results and then we use, in an empirical Bayes spirit, the first four moments of the data to estimate the first four moments ofg(θ). By using sampling techniques we proceed in a fully Bayesian fashion to obtain any posterior summaries of interest. Simulations which investigate the operating characteristics of our proposed methodology are presented. We illustrate our approach using data from mixed Poisson and mixed exponential densities.
Likelihood Inference for Gibbs Processes in the Analysis of Spatial Point Patterns*
Authors: Mateu Jorge , Montes Francisco
Published: May 2007

Several authors have proposed stochastic and non‐stochastic approximations to the maximum likelihood estimate (MLE) for Gibbs point processes in modelling spatial point patterns with pairwise interactions. The approximations are necessary because of the difficulty of evaluating the normalizing constant. In this paper, we first provide a review of methods which yield crude approximations to the MLE. We also review methods based on Markov chain Monte Carlo techniques for which exact MLE has become feasible. We then present a comparative simulation study of the performance of such methods of estimation based on two simulation techniques, the Gibbs sampler and the Metropolis‐Hastings algorithm, carried out for the Strauss model.
Some Cracks in the Empire of Chance (Flaws in the Foundations of Reliability)
Authors: Singpurwalla Nozer D.
Published: May 2007

Making quantified statements about the uncertainty associated with the lifelength of an item is one of the most fundamental tasks of reliability assessment. Most practitioners routinely do this using one of the several available statistical techniques. The purpose of this paper is two‐fold. The first is to give the user an overview of the key tenets of two of the most commonly used parametric approaches. The second is to point out that these commonly used approaches involve strategies that are either ad hoc, or are in violation of some of the underlying tenets. A method that is devoid of logical flaws can be proposed, but this method is difficult to implement. The user must therefore resign to using that technique against which the fewest objections can be hurled.
Estimating Long‐term Trends in Tropospheric Ozone Levels
Authors: Smith Michael , Yau Paul , Shively Thomas , Kohn Robert
Published: May 2007

This paper develops Bayesian methodology for estimating long‐term trends in the daily maxima of tropospheric ozone. The methods are then applied to study long‐term trends in ozone at six monitoring sites in the state of Texas. The methodology controls for the effects of meteorological variables because it is known that variables such as temperature, wind speed and humidity substantially affect the formation of tropospheric ozone. A semiparametric regression model is estimated in which a nonparametric trivariate surface is used to model the relationship between ozone and these meteorological variables because, while it is known that the relatinship is a complex nonlinear one, its functional form is unknown. The model also allows for the effects of wind direction and seasonality. The errors are modeled as an autoregression, which is methodologically challenging because the observations are unequally spaced over time. Each function in the model is represented as a linear combination of basis functions located at all of the design points. We also estimate an appropriate data transformation simulataneously with the functions. The functions are estimated nonparametrically by a Bayesian hierarchical model that uses indicator variables to allow a non‐zero probability that the coefficient of each basis term is zero. The entire model, including the nonparametric surfaces, data transformation and autoregression for the unequally spaced errors, is estimated using a Markov chain Monte Carlo sampling scheme with a computationally efficient transition kernel for generating the indicator variables. The empirical results indicate that key meteorological variables explain most of the variation in daily ozone maxima through a nonlinear interaction and that their effects are consistent across the six sites. However, the estimated trends vary considerably from site to site, even within the same city.
Small Area Estimation‐New Developments and Directions
Authors: Pfeffermann Danny
Published: May 2007

The purpose of this paper is to provide a critical review of the main advances in small area estimation (SAE) methods in recent years. We also discuss some of the earlier developments, which serve as a necessary background for the new studies. The review focuses on model dependent methods with special emphasis on point prediction of the target area quantities, and mean square error assessments. The new models considered are models used for discrete measurements, time series models and models that arise under informative sampling. The possible gains from modeling the correlations among small area random effects used to represent the unexplained variation of the small area target quantities are examined. For review and appraisal of the earlier methods used for SAE, see Ghosh & Rao (1994).
Influence Diagrams for Causal Modelling and Inference
Authors: Dawid A. P.
Published: May 2007

We consider a variety of ways in which probabilistic and causal models can be represented in graphical form. By adding nodes to our graphs to represent parameters, decision,etc., we obtain a generalisation of influence diagrams that supports meaningful causal modelling and inference, and only requires concepts and methods that are already standard in the purely probabilistic case. We relate our representations to others, particularly functional models, and present arguments and examples in favour of their superiority.
Bayesian MCMC Mapping of Quantitative Trait Loci in a Half‐sib Design: a Graphical Model Perspective
Authors: Sheehan N.A. , Gulbrandtsen B. , Lund M.S. , Sorensen D.A.
Published: May 2007

Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task‐specific software may be extremely efficient for any particular analysis, it is often difficult to adapt to new computational challenges. By viewing these genetic applications in a more general framework, many problems can be handled by essentially the same software. This is advantageous in an area where fast methodological development is essential. Once a method has been fully developed and tested, problem‐specific software may then be required. The aim of this paper is to illustrate the potential use of a graphical model approach to genetic analyses by taking a very simple and well‐understood problem by way of example.
Randomized Response, Statistical Disclosure Control and Misclassificatio: a Review
Authors: van den Hout Ardo , van der Heijden Peter G.M.
Published: May 2007

This paper discusses analysis of categorical data which have been misclassified and where misclassification probabilities are known. Fields where this kind of misclassification occurs are randomized response, statistical disclosure control, and classification with known sensitivity and specificity. Estimates of true frequencies are given, and adjustments to the odds ratio are discussed. Moment estimates and maximum Likelihood estimates are compared and it is proved that they are the same in the interior of the parameter space. Since moment estimators are regularly outside the parameter space, special attention is paid to the possibility of boundary solutions. An example is given.
The Effect of using Household as a Sampling Unit
Authors: Clark Robert G. , Steel David G.
Published: May 2007

The effect of sampling people through households is considered. Results on design effects for two stage surveys are reviewed and applied to give design effects of household samples. The main factors that determine the design effect are identified for the designs in which one person, or all people, are selected from each selected household. Within household correlation is one factor. We show that the relationships between household size and the mean and variance within households are also important factors. Census and survey data are used to empirically compare the design effects for a range estimators, variables and designs.
EXISTENCE OF FELLER COCYCLES ON A C*-ALGEBRA
Authors: LINDSAY J. MARTIN , WILLS STEPHEN J.
Published: May 2007

The quantum stochastic differential equation dkt = kt ∘
θαβdΛβα(t)
is considered on a unital C*-algebra,
with separable noise dimension space. Necessary conditions on the matrix of bounded linear maps θ for
the existence of a completely positive contractive solution are shown to be sufficient. It is known that
for completely positive contraction processes, k satisfies such an equation if and only if k is a
regular Markovian cocycle. ‘Feller’ refers to an invariance condition analogous to probabilistic terminology
if the algebra is thought of as a non-commutative topological space.
EQUISINGULARITY AND LAGRANGEAN CURVES
Authors: NETO ORLANDO
Published: May 2007

The most natural candidates to the definition of equisingularity of germs of complex space curves
are discussed, showing that they coincide in the case of Lagrangean curves (projectivizations of conic
Lagrangean varieties of a symplectic manifold of dimension four).
COUNTING HOROBALLS AND RATIONAL GEODESICS
Authors: BELABAS KARIM , HERSONSKY SA'AR , PAULIN FRÉDÉRIC
Published: May 2007

Let M be a geometrically finite pinched negatively curved Riemannian manifold with at least one cusp.
The asymptotics of the number of geodesics in M starting from and returning to a given cusp, and of
the number of horoballs at parabolic fixed points in the universal cover of M, are studied in this paper.
The case of SL(2, ℤ), and of Bianchi groups, is developed.
RESIDUAL PROPERTIES OF FREE PRO-P GROUPS
Authors: BARNEA YIFTACH
Published: May 2007

Recall that if S is a class of groups, then a group G is residually-S if,
for any element 1 ≠ g ∈ G, there is a normal subgroup
N of G such that g ∉ N and G/N ∈ S.
Let Λ be a commutative Noetherian local pro-p ring, with a maximal ideal M.
Recall that the first congruence subgroup of SLd(Λ) is:
SL1d(Λ)
= ker (SLd(Λ) → SLd(Λ/M)).

Let K ⊆ ℕ. We define SΛ(K)
= ∪d∈K{open subgroups of SL1d(Λ)}.
We show that if K is infinite, then for Λ = [ ]p[[t]]
and for Λ = ℤp a finitely generated non-abelian free pro-p group is
residually-SΛ(K). We
apply a probabilistic method, combined with Lie methods and a result on random generation in simple
algebraic groups over local fields. It is surprising that the case of zero characteristic is deduced from the
positive characteristic case.
HYPERCENTRAL GROUPS WITH ALL SUBGROUPS SUBNORMAL III
Authors: SMITH HOWARD
Published: May 2007

It is shown that a hypercentral group that has all subgroups subnormal and every non-nilpotent subgroup
of bounded defect is nilpotent. As a consequence, a hypercentral group of length at most ω in which
every subgroup is subnormal is nilpotent.