bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayes Convolution
Authors: van den Heuvel Edwin R. , Klaassen Chris A. J. 
Published: May 2007

SummaryA general convolution theorem within a Bayesian framework is presented. Consider estimation of the Euclidean parameter θ by an estimator T within a parametric model. Let W be a prior distribution for θ and define G as the W‐average of the distribution of T ‐ θ under θ. In some cases, for any estimator T the distribution G can be written as a convolution G = K * L with K a distribution depending only on the model, i.e. on W and the distributions under θ of the observations. In such a Bayes convolution result optimal estimators exist, satisfying G = K. For location models we show that finite sample Bayes convolution results hold in the normal, loggamma and exponential case. Under regularity conditions we prove that normal and loggamma are the only smooth location cases. We also discuss relations with classical convolution theorems.
Estimating Capital Inputs for Productivity Measurement: An Overview of U.S. Concepts and Methods
Authors: Harper Michael J. 
Published: May 2007

SummaryThe U.S. Bureau of Labor Statistics (BLS) publishes measures of multifactor productivity, which are patterned after the Solow residual. Inputs of capital must be aggregated with inputs of labor. The theory requires a measure of the capital service flow, a rather abstract notion which is rarely observable. The BLS procedures for capital measurement are summarized, and the rationale for these procedures is explored. Implicit measures of capital services are derived from data on property income and data on historical investments which are detailed as to type of asset.
Indicators, Green Accounting and Environment Statistics— Information Requirements for Sustainable Development
Authors: Radermacher Walter 
Published: May 2007

SummarySince the “Earth Summit” in Rio de Janeiro 1992 the term “sustainable development” determines the third and current phase of environmental policy. A precise and commonly accepted definition of sustainable development (s.d.) is still missing. There are, nevertheless, some elements in the philosophy of sustainable development which–even if they are still vague–could be used as guidelines for a framework of “green” accounting and sustainability indicators. Based on theoretical considerations, the German Federal Statistical Office has developed a framework for an Environmental Economic Accounting System. The objective is to add meaningful modules to the traditional System of National Accounts which are designed to quantify the external (environmental) effects of economic activities. The framework could already be realised and published to an extent that is relevant for actual policy making in Germany.
The Early History of the Cumulants and the Gram‐Charlier Series
Authors: Hald Anders 
Published: May 2007

SummaryThe early history of the Gram‐Charlier series is discussed from three points of view: (1) a generalization of Laplace's central limit theorem, (2) a least squares approximation to a continuous function by means of Chebyshev‐Hermite polynomials, (3) a generalization of Gauss's normal distribution to a system of skew distributions. Thiele defined the cumulants in terms of the moments, first by a recursion formula and later by an expansion of the logarithm of the moment generating function. He devised a differential operator which adjusts any cumulant to a desired value. His little known 1899 paper in Danish on the properties of the cumulants is translated into English in the Appendix.
Sick‐leave and Other Job‐related Health Issues from Labour Force Surveys Data
Authors: Campostrini Stefano , Bellini Pierantonio 
Published: May 2007

SummaryMost research into the relationship between health and work has been limited to ad hoc studies: few studies have been based on large‐sample surveys directed to the general population. We propose here approaches to developing work‐related health indicators from currently collected National Labour Force Surveys, in particular the Italian Labour Force Survey‐ISTAT. Four potential indicators are proposed: temporary reduction in working ability (TRWA), continued reduction in working ability (CRWA), permanent inability to work (PIW), and exclusion from the active population (EAP). Our analysis indicates that CRWA and EAP are highest among manual workers, consistent with the well‐described relationship between job class and health status. This approach provides an opportunity to monitor the relative health status of workers on a continuing basis using readily available, population‐based data and to conduct additional analyses on the basis of occupational stratification.
Australian Commonwealth Government Statistical Clearing House: Vehicle for Reducing Response Load and Improving Survey Quality
Authors: Colledge Michael J. , Starick Rosslyn 
Published: May 2007

SummaryThe recently constituted Commonwealth Government Statistical Clearing House was set up in response to a small business task force recommendation. It is operated by the Australian Bureau of Statistics (ABS) as part of that agency's coordination role. Its primary goal is to ensure that surveys impose minimum load on business respondents and that the data collected are fit for their intended uses. Surveys affecting 50 or more businesses conducted by or on behalf of Australian Government departments or agencies, including the ABS itself, are subject to a clearance process. Those that are not approved are not permitted to start or continue. Statistical Clearing House review procedures not only aim to reduce respondent load and promote good design, they also ensure good documentation and facilitate data sharing. Metadata descriptions of all the surveys subject to review are recorded in the Commonwealth Register of Surveys of Businesses, publicly accessible via the Internet.This paper augments and updates previously published material. It outlines the objectives, development and operation of the Statistical Clearing House from the perspective of its contribution to reduction in respondent load and improvement in survey quality. It describes the review criteria and the survey metadata that are required to support the clearance process. It briefly compares and contrasts similar programs at other statistical agencies. Finally, it summarises the first year of operations. The tentative conclusion is that the benefits brought by the program in terms of increased survey taker awareness of respondent load and quality issues outweigh the additional work required by survey managers to comply with the program and the costs of administering it.
Realistic Statistical Modelling of Financial Data
Authors: Rydberg Tina Hviid 
Published: May 2007

SummaryThe aim of this paper is to present some of the stylized features of financial data which have received a lot of attention both from practitioners and those with more theoretical backgrounds. Some of the models resulting from these efforts are reviewed and discussed. To facilitate the discussion two data sets are used: one of these contains all US trades in IBM stocks in 1995 at NYSE.
Microsimulation of Business Performance
Authors: Kokic Philip , Chambers Ray , Beare Steve 
Published: May 2007

SummaryMicrosimulation of business performance based on sample survey data is a relatively underdeveloped field, but its application in government economic policy formulation is potentially great since it can be used to measure the distributional effects of change rather than just average change. Techniques which account for the dynamic response of businesses to macro level price expectations have recently been developed (Kokic et al., 1993). These allow individual level business performance to be forecast from sample survey data. In this paper we outline a general methodology for combining these forecasting techniques with Monte Carlo simulation in order to produce a microsimulation of business performance that accurately captures the true distributional characteristics of the underling survey data. Applying this methodology to Australian farm survey data, we show that these methods may be used to forecast the distribution of farm business production and performance within arbitrary subdomains of the surveyed population conditional on a given set of expected commodity price outcomes. The microsimulations reflect both the uncertainty due to climatic variation from one year to the next, which in the Australian context depends largely on geographic location, as well as the uncertainty of commodity prices.
Ten More Years of Error Rate Research
Authors: Schiavo Rosa A. , Hand David J. 
Published: May 2007

SummaryThe assessment of the performance of supervised classification rules by estimating their error rate (the proportion of objects misclassified) is an important area of work in statistical pattern recognition. This paper reviews the last ten years of error rate research, bringing up to date the reviews of Hand (1986a) and McLachlan (1987). Since those surveys were published, old estimators have been improved new estimators have been introduced, and new approaches to error rate estimation have been developed. Some of this work has led to deep insights into classification methodology and statistical modelling in general.
Designs for Variance Components Estimation: Past and Present
Authors: Khuri André I. 
Published: May 2007

SummaryThis article provides (1) a comprehensive coverage of the literature on designs for estimating variance components, and (2) a review of recent applications of such designs in genetics, statistical process control, and quality improvement. In addition, recent methods of estimation of variance components and model forms, other than the linear, are discussed. The latter developments have a direct effect on the choice of design. Some suggested ideas for future research directions are also given.
Generalized Symmetry Models for Hypercubic Concordance Tables
Authors: Lovison Gianfranco 
Published: May 2007

SummaryFrequency data obtained classifying a sample of ‘units’ by the same categorical variable repeatedly over ‘components’, can be arranged in ahypercubic concordance table (h.c.t.). This kind of data naturally arises in a number of different areas such as longitudinal studies, studies using matched and clustered data, item‐response analysis, agreement analysis. In spite of the substantial diversity of the mechanisms that can generate them, data arranged in a h.c.t. can all be analyzed via models of symmetry and quasi‐symmetry, which exploit the special structure of the h.c.t. The paper extends the definition of such models to any dimension, introducing the class ofgeneralized symmetry models, which provides a unified framework for inference on categorical data that can be represented in a h.c.t., Within this framework it is possible to derive the common structure which underlies these models and clarify their meaning; their usefulness in applied work is illustrated by a re‐analysis of two real examples.
Investigation of Linkage and Association‐Issues on Study Design
Authors: Bickeböller Heike 
Published: May 2007

SummaryFor the identification and description of susceptibility genes for complex diseases using genetic markers there are two basic strategies: genome scans or the investigation of candidate genes. The designs can be quite different for the two approaches and decide, more than in general epidemiology, the methods that can be applied subsequently. Study design, recruitment and sample size are discussed further in the context of the Transmission/Disequilibrium Test, a family‐based simultaneous test for linkage and association.
An Introduction to Coding Theory and the Two‐Part Minimum Description Length Principle
Authors: Lee Thomas C. M. 
Published: May 2007

SummaryThis article provides a tutorial introduction to the so‐called two‐part minimum description length (MDL) principle proposed by Rissanen. This two‐part MDL principle is a powerful methodology for solving many statistical model selection problems. However, it seems that this powerful methodology is only adopted by a small number of statisticians to tackle a small number of problems. One plausible reason for this is that the coding theory results required by the MDL principle are somewhat new to most statisticians, and that there are not many readily accessible articles introducing these results appearing in the statistical literature. The first part of this article is devoted to a discussion of such coding theory results. Then, in the second part of the article, the two‐part MDL principle is introduced and explained. In doing so, only those coding theory results that are presented in the first part of the article are used. Finally, the applicability of the two‐part MDL principle is demonstrated by applying it to tackle four different statistical problems.
Competitive On‐line Statistics
Authors: Vovk Volodya 
Published: May 2007

SummaryA radically new approach to statistical modelling, which combines mathematical techniques of Bayesian statistics with the philosophy of the theory of competitive on‐line algorithms, has arisen over the last decade in computer science (to a large degree, under the influence of Dawid's prequential statistics). In this approach, which we call “competitive on‐line statistics”, it is not assumed that data are generated by some stochastic mechanism; the bounds derived for the performance of competitive on‐line statistical procedures areguaranteedto hold (and not just hold with high probability or on the average). This paper reviews some results in this area; the new material in it includes the proofs for the performance of the Aggregating Algorithm in the problem of linear regression with square loss.
A Bayesian Model for Estimating Census Undercount, Taking Emigration Data from Foreign Censuses*
Authors: Redfern Philip 
Published: May 2007

SummaryThe new method of measuring net undercount in a census of population is a variant of demographic analysis and is founded in the belief that the most reliable counts of people are the counts of births and deaths. It has been applied to the 1991 census of England and Wales (E&W). The method has two distinctive features. The first is that it bases its estimates of numbers of emigrants on figures of persons born here and recorded as residents in the 1990–91 censuses of other countries. The corresponding data on immigrants are taken from our own census. The method does not therefore require the data on migratory flows that are an essential component of conventional demographic analysis. The second feature is the Bayesian approach in which (1) each of 30 uncertain elements in the calculations is given an a priori error distribution and (2) three empirical constraints are imposed on the sex‐age profile of percentage net undercount. This, in conjunction with a Monte Carlo process, generates an error distribution for net undercount. These merits of the method are offset by the demerit that the calculations must await results from the censuses of the other countries in which substantial numbers of our emigrants reside.
Modeling Clustered Ordered Categorical Data: A Survey
Authors: Agresti Alan , Natarajan Ranjini 
Published: May 2007

SummaryThis article surveys various strategies for modeling ordered categorical (ordinal) response variables when the data have some type of clustering, extending a similar survey for binary data by Pendergast, Gange, Newton, Lindstrom, Palta & Fisher (1996). An important special case is when repeated measurement occurs at various occasions for each subject, such as in longitudinal studies. A much greater variety of models and fitting methods are available than when a similar survey for repeated ordinal response data was prepared a decade ago (Agresti, 1989). The primary emphasis of the review is on two classes of models,marginal modelsfor which effects are averaged over all clusters at particular levels of predictors, andcluster‐specific modelsfor which effects apply at the cluster level. We present the two types of models in the ordinal context, review the literature for each, and discuss connections between them. Then, we summarize some alternative modeling approaches and ways of estimating parameters, including a Bayesian approach. We also discuss applications and areas likely to be popular for future research, such as ways of handling missing data and ways of modeling agreement and evaluating the accuracy of diagnostic tests. Finally, we review the current availability of software for using the methods discussed in this article.
Modelling Overdispersion for Complex Survey Data
Authors: Molina E.A. , Smith T.M.F. , Sugden R.A. 
Published: May 2007

SummaryThe population characteristics observed by selecting a complex sample from a finite identified population are the result of at least two processes: the process which generates the values attached to the units in the finite population, and the process of selecting the sample of units from the population. In this paper we propose that the resulting observations by viewed as the joint realization of both processes. We overcome the inherent difflculty in modelling the joint processes of generation and selection by exploring second moment and other simplifying assumptions. We obtain general expressions for the mean and covariance function of the joint processes and show that several overdispersion models discussed in the literature for the analysis of complex surveys are a direct consequence of our formulation, undere particular sampling schemes and population structures.
Idiot's Bayes—Not So Stupid After All?
Authors: Hand David J. , Yu Keming 
Published: May 2007

SummaryFolklore has it that a very simple supervised classification rule, based on the typically false assumption that the predictor variables are independent, can be highly effective, and often more effective than sophisticated rules. We examine the evidence for this, both empirical, as observed in real data applications, and theoretical, summarising explanations for why this simple rule might be effective.
Statistics by Gender: Measures to Reduce Gender Bias in Agricultural Surveys
Authors: Ayhan H. Öztş 
Published: May 2007

SummaryStatistics by gender has been the concern of policy makers in the recent past years. The demand on data disaggregated by gender has led the survey statistician to collect data and tabulate statistics by gender. In this paper, some measures will be suggested to avoid and reduce gender bias for data collection and tabulation in agricultural surveys.
Crucial Issues for Statistics in the Next Two Decades
Authors: Fisher Nicholas I. 
Published: May 2007

SummaryThis collection of articles stems from an Invited Paper meeting at the 52nd Session of the ISI in Helsinki, August 1999. The purpose of the session was to explore issues likely to be critical to the long‐term survival of the discipline, if not the profession, of Statistics. The contributors in the session have all made outstanding contributions to both the theory and practice of Statistics, and have also had an ongoing interest in the long‐term development of the subject. Subsequently, they were given the opportunity to elaborate on their contributions, for wider dissemination.
The Role of Statistics in the Data Revolution?
Authors: Friedman Jerome H. 
Published: May 2007

SummaryThe nature of data is rapidly changing. Data sets are becoming increasingly large and complex. Modern methodology for analyzing these new types of data are emerging from the fields of Data Base Managment, Artificial Intelligence, Machine Learning, Pattern Recognition, and Data Visualization. So far Statistics as a field has played a minor role. This paper explores some of the reasons for this, and why statisticians should have an interest in participating in the development of new methods for large and complex data sets.
Future Directions for the Teaching and Learning of Statistics at the Tertiary Level
Authors: Nicholl Des F. 
Published: May 2007

SummarySignificant advances in, and the resultant impact of, Information Technology (IT) during the last fifteen years has resulted in a much more data based society, a trend that can be expected to continue into the foreseeable future. This phenomenon has had a real impact on the Statistics discipline and will continue to result in changes in both content and course delivery. Major research directions have also evolved during the last ten years directly as a result of advances in IT. The impact of these advances has started to flow into course content, at least for advanced courses. One question which arises relates to what impact will this have on the future training of statisticians, both with respect to course content and mode of delivery. At the tertiary level the last 40 years has seen significant advances in theoretical aspects of the Statistics discipline. Universities have been outstanding at producing scholars with a strong theoretical background but questions have been asked as to whether this has, to some degree, been at the expense of appropriate training of the users of statistics (the ‘tradespersons’).Future directions in the teaching and learning of Statistics must take into account the impact of IT together with the competing need to produce scholars as well as competent users of statistics to meet the future needs of the market place. For Statistics to survive as a recognizable discipline the need to be able to train statisticians with an ability to communicate is also seen as an areà of crucial importance.Satisfying the needs of society as well as meeting the needs of the profession are considered as the basic determinants which will derive the future teaching and training of statisticians at the tertiary level and will form the basis of this presentation.
Public Policy Issues as a Route to Statistical Awareness
Authors: Smith Adrian F.M. 
Published: May 2007

SummaryThere appears to be a paradox in the fact that as more and more quantitative information becomes routinely available in a world perceived to be ever more complex, there is less and less direct appreciation of the role and power of statistical thinking. It is suggested that the profession should exploit very real public concerns regarding risk aspects of public policy as a possible pedagogic route to raising statistical awareness.
A Guide to Exact Simulation
Authors: Dimakos Xeni K. 
Published: May 2007

SummaryMarkov Chain Monte Carlo (MCMC) methods are used to sample from complicated multivariate distributions with normalizing constants that may not be computable in practice and from which direct sampling is not feasible. A fundamental problem is to determine convergence of the chains. Propp & Wilson (1996) devised a Markov chain algorithm called Coupling From The Past (CFTP) that solves this problem, as it produces exact samples from the target distribution and determines automatically how long it needs to run. Exact sampling by CFTP and other methods is currently a thriving research topic. This paper gives a review of some of these ideas, with emphasis on the CFTP algorithm. The concepts of coupling and monotone CFTP are introduced, and results on the running time of the algorithm presented. The interruptible method of Fill (1998) and the method of Murdoch & Green (1998) for exact sampling for continuous distributions are presented. Novel simulation experiments are reported for exact sampling from the Ising model in the setting of Bayesian image restoration, and the results are compared to standard MCMC. The results show that CFTP works at least as well as standard MCMC, with convergence monitored by the method of Raftery & Lewis (1992, 1996).