bluuebunny/crossref_metadata_2025 huggingface dataset:
Teachers All: Samoan, Fijian, and Queensland Melanesian Missionaries in Papua, 1884–1914
Authors: Wetherell David
Published: March 2003

Pacific Islands mission teachers were powerful agents of culture change in Oceania, and the Christianity they taught is part of the ideological and constitutional under‐pinnings of several independent Pacific Island states. Their fullest impact was felt in the period between the 1880s and 1914, when vast distances were being crossed and diverse populations reached by evangelists from half a dozen Pacific nationalities. Below the common religious motivations professed by the Islands teachers there were sharp contrasts in expectations and behaviour. This paper compares the Samoan, Fijian, and Queensland Melanesian missionaries in Papua, a colony where Islanders were concentrated in larger numbers than elsewhere. The Samoans are given the greater balance of analysis in the paper, because the 187 male Samoans outnumbered both the Fijians (110 males) and Queensland Melanesians (46), and because the Samoans’ expectations diverged more sharply from those of their Euro‐pean colleagues than was the case with their Fijian and Queensland Melanesian contemporaries.
Australian Catholics and Conscription in the Great War
Authors: Kildea Jeff
Published: March 2003

During the Great War the Australian people twice voted to reject conscription for overseas military service. In the historiography of those plebiscites it is generally accepted that most Catholics opposed compulsion because of their Irish and working class backgrounds rather than their religion. However, in December 1917, members of the Catholic hierarchy and official church institutions, who had been silent during the first plebiscite in October 1916, actively campaigned against conscription because the government’s proposal did not exempt teaching brothers and seminarians. Although their opposition had nothing to do with theology, its source was religion rather than ethnicity, class, or national sentiment. This article examines the bishops’ concern, challenging the notion that they used it as a convenient excuse to abandon their neutrality in order to be re–united politically with their people, and argues that they did so out of a legitimate concern for the welfare of their church.
Resurrection of the Body: Eleventh–Century Evidence from the Sermons of Ademar of Chabannes
Authors: Frassetto Michael
Published: March 2003

The matter of the resurrection of the body was an issue of central concern to medieval Christians, as Carolyn Bynum and others have shown. Most scholars, however, have neglected to consider attitudes around the year 1000. The sermons of Ademar of Chabannes (989–1034) provide insight into early eleventh–century beliefs, and therefore this paper examines his understanding of the resurrected body. Ademar was drawn to the matter of the resurrection for several reasons, including a sense that he was living in the last days and his failure in the debate over the apostolicity of Saint Martial. His understanding of the nature of the resurrected body was also shaped by traditional church teaching, especially the Apostles’ Creed, which he defended in sermons against his perception of the denial of the material world by the “Manichaeans” of Aquitaine. Ademar also used the cult of the saints to demonstrate the reality of the physical resurrection of the body.
“Days of Heaven on Earth”: Presbyterian Communion Seasons in Nineteenth–Century Otago
Authors: Clarke Alison
Published: March 2003

Communion seasons were a distinctive and important part of nineteenth–century Presbyterian culture. This paper examines such occasions in the Presbyterian–dominated colony of Otago, New Zealand. Communion was a significant social event, and its preparatory fast days were holidays for the whole community. As a spiritual event, the communion season induced an experiential and emotive piety, belying common modern perceptions of nineteenth–century Presbyterianism as an ascetic and intellectualised faith. Over the period from the founding of the colony (1848) to the turn of the century, certain rituals of the communion season altered significantly. Some changes occurred in response to new ideologies such as temperance; others reflected a softening of traditional Calvinist theology in favour of a more inclusive religion, Presbyterians being invited to communion rather than having to prove themselves fit to attend. Such changes were not unique to Otago, and practice in the colony reveals a strong continuity with events in Scotland: the Presbyterian communion season proved a remarkably successful import to colonial Otago.
Metalinguistic Awareness, Reading and Spelling: Roots and Branches of Literacy
Authors: Lazo Monica G. , Pumfrey Peter D. , Peers Ian
Published: March 2003

Studies on the role of metalinguistic awareness in emerging literacy have established that metalinguistic abilities at phonological, syntactic, print and pragmatic levels are linked to later attainments in literacy. Few have examined the interplay among these skills and developing reading and spelling. Using time‐reversed path analyses, this study explores the possibility that metalinguistic awareness registers stronger direct effects on literacy than early pre‐conventional reading and invented spelling skills. Sixty children aged 54 months (initially) were given measures of metalinguistic abilities, pre‐conventional reading and invented spelling on three occasions. This allowed the exploration of reciprocal relationships between pre‐conventional reading, invented spelling and metalinguistic abilities. On the fourth occasion, standardised tests of reading and spelling were administered. Results from time‐reversed path analysis show that pre‐conventional reading and invented spelling influenced each other across development and had stronger direct effects on subsequent literacy than did aspects of metalinguistic awareness. Pre‐literate metalinguistic abilities were shown to affect pre‐conventional reading and invented spelling skills and combine with these to influence further growth in literacy. The study’s results have implications for current models of literacy development.
Baseline assessment of writing: the need for reconsideration
Authors: Nutbrown Cathy
Published: March 2003

This article questions the usefulness to teaching of items to be used in baseline assessment of writing in the UK. Current requirements for national baseline assessment are intended to serve two very different purposes: assessment for management and assessment for teaching. It is argued that this duality of purpose can threaten teaching and overemphasise assessment for management. This article describes a small study investigating items on the baseline assessment scale developed by the Schools Curriculum and Assessment Authority (SCAA, 1997a), which suggests that the SCAA criteria for baseline assessment of writing need to be reconsidered. This reconsideration can be sought in the light of research and evidence of children’s achievements. Finally the paper concludes that there needs to be greater clarity of purpose and a redefinition of the misleading term ‘baseline assessment’.
Decline in Average Reading Scores in Year 6 in One Area (Research Note)
Authors: Davies Julie
Published: March 2003

This study examines the reading standards of eight cohorts (years 1989 to 1996) of Year 6 children (mean age 11.31) from five randomly selected primary schools within one Local Education Authority in England. The total size of the sample was 1,503 children. The analysis focuses on the extent to which average scores in reading comprehension have changed over the eight years from 1989 to 1996. Examination of the means of the standardised comprehension scores for each cohort reveals a significant fall in attainment between Cohort 1 (1989), on the one hand, and Cohorts 6 (1994) and 7 (1995), on the other. The percentage of children with scores greater that one standard deviation above the mean (i.e. above standard score 115) declined from 22 per cent in Cohort 1 (1989) to 7 per cent in Cohort 6 (1994), with a similar increased in the percentage of children scoring less than one standard deviation below the mean. The implications of these findings are briefly discussed.
Naming speed and word familiarity as confounding factors in decoding
Authors: Joshi R. Malatesha , Aaron P. G.
Published: March 2003

The present investigation has three aims: (1) to establish a suitable composite index which combines speed and accuracy in the measurement of decoding skill; (2) to examine whether speed acts as a confounding factor in the measurement of decoding ability; and (3) to see whether familiarity with the word, as indicated by the ability to pronounce it, or lack of it acts as a confounding factor in the assessment of spelling skills. Three studies were conducted to fulfill these aims. In the first study, 33 children from Grade 2 were asked to name a list of 40 letters of the alphabet as quickly and as accurately as possible. A combined index of speed and accuracy was computed from these two sets of data using two formulas, which were based on the ‘z’ score and the mean variance score. A Pearson product‐moment correlation coefficient of 0.94 was obtained between the results of the two formulas indicating that the two formulas yield almost identical results. In the second study, 37 fifth‐graders were administered the word‐attack sub‐test of Woodcock Language Proficiency Battery. When the speed and accuracy composite index, based on the ‘z formula’ was applied to the word‐attack scores, it was found that three children were slow decoders even though their scores were within the normal range. In the third study, 39 children from Grade 3 and 40 children from Grade 5 were asked to read aloud a list of words and then these words were administered as a spelling test. Subsequently, their spelling ability was assessed by computing the number of words they could both read and spell correctly. When familiarity of words was included as a factor in assessing spelling ability, five children in Grade 3 and three children in Grade 5 were found to be misclassified as poor spellers. This indicates that including word‐naming speed and word familiarity (i.e. ability to pronounce) produce different metrics than when they are not. Inclusion of speed and familiarity factors in assessment can be helpful in avoiding false negatives and false positives.
The Influence of Behavioural Heterogeneity on the Population Level Effect of Potential Prophylactic Human Immunodeficiency Virus Type 1 Vaccines
Authors: Garnett G. P.
Published: March 2003

Theoretical results indicate that extensive coverage with low efficacy type 1 human immunodeficiency virus (HIV) vaccines could substantially reduce the incidence of HIV in developing countries. There is a non-linear relationship between effective vaccine coverage and HIV prevalence such that improved efficacy brings diminishing returns. The relative contribution of HIV-associated mortality and behavioural heterogeneity to this non-linear relationship is explored using deterministic mathematical models. If the duration of risk of acquiring HIV is long relative to the HIV incubation period then infection-associated mortality can generate the non-linear relationship. However, in its absence the same relationship results from behavioural heterogeneity. Models of HIV vaccination alongside other interventions generate qualitative results that suggest that targeted interventions lead to less redundancy in control efforts.
Measuring Sexual Partner Networks for Transmission of Sexually Transmitted Diseases
Authors: Ghani A. C. , Garnett G. P.
Published: March 2003

Patterns of sexual mixing and the sexual partner network are important determinants of the spread of all sexually transmitted diseases (STDs), including the human immunodeficiency virus. Novel statistical problems arise in the analysis and interpretation of studies aimed at measuring patterns of sexual mixing and sexual partner networks. Samples of mixing patterns and network structures derived from randomly sampling individuals are not themselves random samples of measures of partnerships or networks. In addition, the sensitive nature of questions on sexual activity will result in the introduction of non-response biases, which in estimating network structures are likely to be non-ignorable. Adjusting estimates for these biases by using standard statistical approaches is complicated by the complex interactions between the mechanisms generating bias and the non-independent nature of network data. Using a two-step Monte Carlo simulation approach, we have shown that measures of mixing patterns and the network structure that do not account for missing data and non-random sampling are severely biased. Here, we use this approach to adjust raw estimates in data to incorporate these effects. The results suggest that the risk for transmission of STDs in empirical data is underestimated by ignoring missing data and non-random sampling.
Monitoring Contemporary Student Flows and Characteristics: Secondary Analyses Using the Labour Force Survey and the General Household Survey
Authors: Egerton Muriel
Published: March 2003

This paper examines trends in the participation in higher education by disadvantaged social groups over the recent period of higher education expansion and reform. It has been suggested that disadvantaged groups can recoup by participation at mature ages and this question is examined. The data sources used are the Labour Force Survey (1986–1995), which yielded 13384 students (6747 men and 6637 women) and the General Household Survey (1984–1992) which yielded 1936 students (982 men and 954 women). From a perspective of equal opportunities, the relative participation of young people from manual and non-manual origins does not appear to have changed over the period considered, but there is some evidence of increased relative participation by people from manual class origins as mature students. Mature students from such origins were older than those from non-manual class origins, as were mature women than mature men, with consequences for employability. From a perspective of lifelong learning, the recent expansion has been successful, with more entrants from the unemployed. Considerable percentages of women also enter from full-time housework, and increasing percentages from manual work. However, as in the past, many entrants had been successful in becoming employed before entry, some being seconded by employers. Despite these changes, the greatest absolute take-up has been from middle class youth. Early employment outcomes were examined and suggest some discrimination against mature students. It is possible that the increased cost of higher education, in the context of an expanded labour market of graduates, may deter some mature students.
The Social Class of Catholics in Scotland
Authors: Paterson Lindsay
Published: March 2003

The social status of people brought up as Catholics in Scotland, as measured by their occupational class, is analysed by using cross-sectional survey data gathered in 1997. The main finding is that Catholics have probably risen in social status to a greater extent than non-Catholics. The experience of Scottish Catholics seems to be distinctive, because no such patterns are found for England, and indeed in this respect Scottish Catholics more closely resemble members of non-Christian religions in England than they do English Catholics. The most likely explanation is the particular role which state-funded Catholic schools have played in Scotland, especially the system of comprehensive secondary schools that was set up after 1965. However, the analysis is suggestive rather than definitive and needs to be replicated on cohort data with larger sample sizes.
A Parallel Analysis of Individual and Ecological Data on Residential Radon and Lung Cancer in South-West England
Authors: Darby Sarah , Deo Harz , Doll Richard , Whitley Elise
Published: March 2003

Parallel individual and ecological analyses of data on residential radon have been performed using information on cases of lung cancer and population controls from a recent study in south-west England. For the individual analysis the overall results indicated that the relative risk of lung cancer at 100 Bq m−3 compared with at 0 Bq m−3 was 1.12 (95% confidence interval (0.99, 1.27)) after adjusting for age, sex, smoking, county of residence and social class. In the ecological analysis substantial bias in the estimated effect of radon was present for one of the two counties involved unless an additional variable, urban–rural status, was included in the model, although this variable was not an important confounder in the individual level analysis. Most of the methods that have been recommended for overcoming the limitations of ecological studies would not in practice have proved useful in identifying this variable as an appreciable source of bias.
Detecting Covariates with Non-Random Missing Values in a Survey of Primary Education in Madagascar
Authors: Lindsey J. K. , Lindsey P. J.
Published: March 2003

A major survey of the determinants of access to primary education in Madagascar was carried out in 1994. The probability of enrolment, probability of admission, delay before beginning school, probability of repeating a year and probability of dropping out were studied. The results of the survey are briefly described. In the analysis, one major problem was non-random missing values in the covariates. Some simple methods were developed for detecting whether a response variable depends on the missingness of a given covariate and whether eliminating the missing values would distort the resulting model. A way of incorporating covariates with randomly missing values was used such that the individuals having the missing values did not need to be eliminated. These methods are described and examples are given on how they were applied for one of the key covariates that had a large number of non-random missing values and for one for which the values appear to be randomly missing.
Decline and Fall: Unemployment among Britain’s Non-White Ethnic Communities 1960–1999
Authors: Leslie Derek , Lindley Joanne , Thomas Leighton
Published: March 2003

The declining employment fortunes of Britain’s non-white communities, relative to whites, are explained. To achieve this comparison, some historical official sources of unemployment data are reviewed. The earliest known official time series on unemployment of non-whites dates back to 1960. This historical context is explored, especially the reluctance to make the early data more widely known. An unemployment series for non-white males and females from 1970 to 1999 is derived in two separate ways by splicing together official sources. These series are compared with unemployment of whites to demonstrate a relative increase in unemployment of non-whites.
Some New International Comparisons of Productivity Performance at the Sectoral Level
Authors: Malley Jim , Muscatelli Anton , Woitek Ulrich
Published: March 2003

We present several new measures of gross-output-based total factor productivity (TFP) at the sectoral level for manufacturing industries in the G-7 economies. We calculate measures of both TFP growth and comparative levels. These are obtained by combining conventional Organisation for Economic Co-operation and Development sectoral data on labour and capital inputs with data on intermediate inputs from national input–output tables. Additionally, we derive cyclically corrected measures of TFP growth. Our evidence shows that the considerable gap in TFP between the USA and other G-7 economies is closing but remains significant.
Transactions of the Statistical Society of London(1837)
Authors: Rosenbaum Sidney
Published: March 2003

The Transactions of the Statistical Society of London (1837) appeared before the journal of the Royal Statistical Society began publication and represents the substantial statistical work that had been undertaken in the early years of the existence of the Society. The contents of this publication are summarized here against the historical background of the time.
Simple Fitting Algorithms for Incomplete Categorical Data
Authors: Molenberghs Geert , Goetghebeur Els
Published: March 2003

A popular approach to estimation based on incomplete data is the EM algorithm. For categorical data, this paper presents a simple expression of the observed data log-likelihood and its derivatives in terms of the complete data for a broad class of models and missing data patterns. We show that using the observed data likelihood directly is easy and has some advantages. One can gain considerable computational speed over the EM algorithm and a straightforward variance estimator is obtained for the parameter estimates. The general formulation treats a wide range of missing data problems in a uniform way. Two examples are worked out in full.
A Robust Test for Non-nested Hypotheses
Authors: Victoria-Feser Maria-Pia
Published: March 2003

We propose a robust version of Cox-type test statistics for the choice between two non-nested hypotheses. We first show that the influence of small amounts of contamination in the data on the test decision can be very large. Secondly, we build a robust test statistic by using the results on robust parametric tests that are available in the literature and show that the level of the robust test is stable. Finally, we show numerically not only the robustness of this new test statistic but also that its asymptotic distribution is a good approximation of its sample distribution, unlike for the classical test statistic. We apply our results to the choice between a Pareto and an exponential distribution as well as between two competing regressors in the simple linear regression model without intercept.
On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion)
Authors: Richardson Sylvia. , Green Peter J.
Published: March 2003

New methodology for fully Bayesian mixture analysis is developed, making use of reversible jump Markov chain Monte Carlo methods that are capable of jumping between the parameter subspaces corresponding to different numbers of components in the mixture. A sample from the full joint distribution of all unknown variables is thereby generated, and this can be used as a basis for a thorough presentation of many aspects of the posterior distribution. The methodology is applied here to the analysis of univariate normal mixtures, using a hierarchical prior model that offers an approach to dealing with weak prior information while avoiding the mathematical pitfalls of using improper priors in the mixture context.
A Bayesian Restoration of an Ion Channel Signal
Authors: Hodgson M. E. A.
Published: March 2003

We present a Bayesian method of ion channel analysis and apply it to a simulated data set. An alternating renewal process prior is assigned to the signal, and an autoregressive process is fitted to the noise. After choosing model hyperconstants to yield ‘uninformative’ priors on the parameters, the joint posterior distribution is computed by using the reversible jump Markov chain Monte Carlo method. A novel form of simulated tempering is used to improve the mixing of the original sampler.
Statistical Applications of the Multivariate Skew Normal Distribution
Authors: Azzalini A. , Capitanio A.
Published: March 2003

Azzalini and Dalla Valle have recently discussed the multivariate skew normal distribution which extends the class of normal distributions by the addition of a shape parameter. The first part of the present paper examines further probabilistic properties of the distribution, with special emphasis on aspects of statistical relevance. Inferential and other statistical issues are discussed in the following part, with applications to some multivariate statistics problems, illustrated by numerical examples. Finally, a further extension is described which introduces a skewing factor of an elliptical density.
Asymptotic Separability in Sensitivity Analysis
Authors: Gastwirth Joseph L. , Krieger Abba M. , Rosenbaum Paul R.
Published: March 2003

In an observational study in which each treated subject is matched to several untreated controls by using observed pretreatment covariates, a sensitivity analysis asks how hidden biases due to unobserved covariates might alter the conclusions. The bounds required for a sensitivity analysis are the solution to an optimization problem. In general, this optimization problem is not separable, in the sense that one cannot find the needed optimum by performing a separate optimization in each matched set and combining the results. We show, however, that this optimization problem is asymptotically separable, so that when there are many matched sets a separate optimization may be performed in each matched set and the results combined to yield the correct optimum with negligible error. This is true when the Wilcoxon rank sum test or the Hodges-Lehmann aligned rank test is applied in matching with multiple controls. Numerical calculations show that the asymptotic approximation performs well with as few as 10 matched sets. In the case of the rank sum test, a table is given containing the separable solution. With this table, only simple arithmetic is required to conduct the sensitivity analysis. The method also supplies estimates, such as the Hodges-Lehmann estimate, and confidence intervals associated with rank tests. The method is illustrated in a study of dropping out of US high schools and the effects on cognitive test scores.
Partial Least Squares Estimator for Single-Index Models
Authors: Naik Prasad , Tsai Chih-Ling
Published: March 2003

The partial least squares (PLS) approach first constructs new explanatory variables, known as factors (or components), which are linear combinations of available predictor variables. A small subset of these factors is then chosen and retained for prediction. We study the performance of PLS in estimating single-index models, especially when the predictor variables exhibit high collinearity. We show that PLS estimates are consistent up to a constant of proportionality. We present three simulation studies that compare the performance of PLS in estimating single-index models with that of sliced inverse regression (SIR). In the first two studies, we find that PLS performs better than SIR when collinearity exists. In the third study, we learn that PLS performs well even when there are multiple dependent variables, the link function is non-linear and the shape of the functional form is not known.
Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics
Authors: Barndorff-Nielsen Ole E. , Shephard Neil
Published: March 2003

Non-Gaussian processes of Ornstein–Uhlenbeck (OU) type offer the possibility of capturing important distributional deviations from Gaussianity and for flexible modelling of dependence structures. This paper develops this potential, drawing on and extending powerful results from probability theory for applications in statistical analysis. Their power is illustrated by a sustained application of OU processes within the context of finance and econometrics. We construct continuous time stochastic volatility models for financial assets where the volatility processes are superpositions of positive OU processes, and we study these models in relation to financial data and theory.
Nonparametric Maximum Likelihood Estimation for Shifted Curves
Authors: Rønn Birgitte B.
Published: March 2003

The analysis of a sample of curves can be done by self-modelling regression methods. Within this framework we follow the ideas of nonparametric maximum likelihood estimation known from event history analysis and the counting process set-up. We derive an infinite dimensional score equation and from there we suggest an algorithm to estimate the shape function for a simple shape invariant model. The nonparametric maximum likelihood estimator that we find turns out to be a Nadaraya–Watson-like estimator, but unlike in the usual kernel smoothing situation we do not need to select a bandwidth or even a kernel function, since the score equation automatically selects the shape and the smoothing parameter for the estimation. We apply the method to a sample of electrophoretic spectra to illustrate how it works.
Estimating the Structural Dimension of Regressions Via Parametric Inverse Regression
Authors: Bura Efstathia , Cook R. Dennis
Published: March 2003

A new estimation method for the dimension of a regression at the outset of an analysis is proposed. A linear subspace spanned by projections of the regressor vector X, which contains part or all of the modelling information for the regression of a vector Y on X, and its dimension are estimated via the means of parametric inverse regression. Smooth parametric curves are fitted to the p inverse regressions via a multivariate linear model. No restrictions are placed on the distribution of the regressors. The estimate of the dimension of the regression is based on optimal estimation procedures. A simulation study shows the method to be more powerful than sliced inverse regression in some situations.
Effects of Model Misspecification on Tests of No Randomized Treatment Effect Arising From Cox’s Proportional Hazards Model
Authors: DiRienzo A. G. , Lagakos S. W.
Published: March 2003

We examine the asymptotic and small sample properties of model-based and robust tests of the null hypothesis of no randomized treatment effect based on the partial likelihood arising from an arbitrarily misspecified Cox proportional hazards model. When the distribution of the censoring variable is either conditionally independent of the treatment group given covariates or conditionally independent of covariates given the treatment group, the numerators of the partial likelihood treatment score and Wald tests have asymptotic mean equal to 0 under the null hypothesis, regardless of whether or how the Cox model is misspecified. We show that the model-based variance estimators used in the calculation of the model-based tests are not, in general, consistent under model misspecification, yet using analytic considerations and simulations we show that their true sizes can be as close to the nominal value as tests calculated with robust variance estimators. As a special case, we show that the model-based log-rank test is asymptotically valid. When the Cox model is misspecified and the distribution of censoring depends on both treatment group and covariates, the asymptotic distributions of the resulting partial likelihood treatment score statistic and maximum partial likelihood estimator do not, in general, have a zero mean under the null hypothesis. Here neither the fully model-based tests, including the log-rank test, nor the robust tests will be asymptotically valid, and we show through simulations that the distortion to test size can be substantial.
Spatiotemporal Prediction for Log-Gaussian Cox Processes
Authors: Brix Anders , Diggle Peter J.
Published: March 2003

Space–time point pattern data have become more widely available as a result of technological developments in areas such as geographic information systems. We describe a flexible class of space–time point processes. Our models are Cox processes whose stochastic intensity is a space–time Ornstein–Uhlenbeck process. We develop moment-based methods of parameter estimation, show how to predict the underlying intensity by using a Markov chain Monte Carlo approach and illustrate the performance of our methods on a synthetic data set.
Relative Efficiencies of Kernel and Local Likelihood Density Estimators
Authors: Hall Peter , Tao Terence
Published: March 2003

Local likelihood methods enjoy advantageous properties, such as good performance in the presence of edge effects, that are rarely found in other approaches to nonparametric density estimation. However, as we argue in this paper, standard kernel methods can have distinct advantages when edge effects are not present. We show that, whereas the integrated variances of the two methods are virtually identical, the integrated squared bias of a conventional kernel estimator is less than that of a local log-linear estimator by as much as a factor of 4. Moreover, the greatest bias improvements offered by kernel methods occur when they are needed most—i.e. when the effect of bias is particularly high. Similar comparisons can also be made when high degree local log-polynomial fits are assessed against high order kernel methods. For example, although (as is well known) high degree local polynomial fits offer potentially infinite efficiency gains relative to their kernel competitors, the converse is also true. Indeed, the asymptotic value of the integrated squared bias of a local log-quadratic estimator can exceed any given constant multiple of that for the competing kernel method. In all cases the densities that suffer problems in the context of local log-likelihood methods can be chosen to be symmetric, either unimodal or bimodal, either infinitely or compactly supported, and to have arbitrarily many derivatives as functions on the real line. They are not pathological. However, our results reveal quantitative differences between global performances of local log-polynomial estimators applied to unimodal or multimodal distributions.
A Model Selection Approach for the Identification of Quantitative Trait Loci in Experimental Crosses
Authors: Broman Karl W. , Speed Terence P.
Published: March 2003

We consider the problem of identifying the genetic loci (called quantitative trait loci (QTLs)) contributing to variation in a quantitative trait, with data on an experimental cross. A large number of different statistical approaches to this problem have been described; most make use of multiple tests of hypotheses, and many consider models allowing only a single QTL. We feel that the problem is best viewed as one of model selection. We discuss the use of model selection ideas to identify QTLs in experimental crosses. We focus on a back-cross experiment, with strictly additive QTLs, and concentrate on identifying QTLs, considering the estimation of their effects and precise locations of secondary importance. We present the results of a simulation study to compare the performances of the more prominent methods.
Estimation of Integrated Squared Density Derivatives from a Contaminated Sample
Authors: Delaigle A. , Gijbels I.
Published: March 2003

We propose a kernel estimator of integrated squared density derivatives, from a sample that has been contaminated by random noise. We derive asymptotic expressions for the bias and the variance of the estimator and show that the squared bias term dominates the variance term. This coincides with results that are available for non-contaminated observations. We then discuss the selection of the bandwidth parameter when estimating integrated squared density derivatives based on contaminated data. We propose a data-driven bandwidth selection procedure of the plug-in type and investigate its finite sample performance via a simulation study.
Estimating the Concentration of Propagules of a Plant Pathogen from Soil Dilution Plate Counts when the Response is Non-linear
Authors: Ridout M. S. , Harris D. C.
Published: March 2003

The estimation of micro-organism concentrations from dilution plate data is discussed for situations where expected counts are not proportional to the amount of sample per plate. Aspects of design and analysis are investigated in relation to an alternative non-linear model in which the concentration is given by the slope at the origin. This exponential model generally provides a good fit to available experimental data. Simulations show that estimators based on the model perform well when the response is non-linear and remain reasonably efficient when the response is linear.
Analysis of the Bovine Spongiform Encephalopathy Maternal Cohort Study: Evidence for Direct Maternal Transmission
Authors: Donnelly C. A. , Ghani A. C. , Ferguson N. M. , Wilesmith J. W. , Anderson R. M.
Published: March 2003

In an initial exploratory analysis of the bovine spongiform encephalopathy (BSE) maternal cohort study data we demonstrate several confounding effects in the study design. Given these effects, we assess a variety of statistical models to determine the relative contributions of direct maternal transmission of the aetiological agent of BSE and of genetic susceptibility to the observed maternally enhanced risk of BSE in the offspring of affected dams. To control for the substantial between-herd variation in the risk of exposure to the BSE agent, it is essential that analyses take into account the matched pair structure of the data. Maternal exposure is estimated to be most important in animals born within 150 days of disease onset in their dams. The analysis of a full survival likelihood model indicates that the hypothesis of maternal transmission with no genetic variation in susceptibility fits the data significantly better than the hypothesis of genetically variable susceptibility with no maternal transmission. However, models incorporating both maternal transmission and genetically variable susceptibility fit the data significantly better than pure maternal transmission models. Although genetic susceptibility cannot be excluded as the cause of the cohort study results in the absence of detailed genotyping, the analysis of these study data suggest that low level maternal transmission of BSE is, at least in part, responsible for the significantly enhanced risk of BSE in the offspring of affected dams. Similar results indicating significant maternal transmission in the later stages of the dam incubation period are obtained from the independent analysis of data on the dam–offspring relationships among confirmed BSE cases.
Nonparametric and Non-Linear Models and Data Mining in time Series: A Case-Study on the Canadian Lynx Data
Authors: Lin T. C. , Pourahmadi M.
Published: March 2003

Nonparametric regression methods are used as exploratory tools for formulating, identifying and estimating non-linear models for the Canadian lynx data, which have attained bench-mark status in the time series literature since the work of Moran in 1953. To avoid the curse of dimensionality in the nonparametric analysis of this short series with 114 observations, we confine attention to the restricted class of additive and projection pursuit regression (PPR) models and rely on the estimated prediction error variance to compare the predictive performance of various (non-)linear models. A PPR model is found to have the smallest (in-sample) estimated prediction error variance of all the models fitted to these data in the literature. We use a data perturbation procedure to assess and adjust for the effect of data mining on the estimated prediction error variances; this renders most models fitted to the lynx data comparable and nearly equivalent. However, on the basis of the mean-squared error of out-of-sample prediction error, the semiparametric model Xt=1.08+1.37Xt−1+f(Xt−2)+et and Tong’s self-exciting threshold autoregression model perform much better than the PPR and other models known for the lynx data.
Bayesian Classification of Neolithic Tools
Authors: Dellaportas Petros
Published: March 2003

The classification of Neolithic tools by using cluster analysis enables archaeologists to understand the function of the tools and the technological and cultural conditions of the societies that made them. In this paper, Bayesian classification is adopted to analyse data which raise the question whether the observed variability, e.g. the shape and dimensions of the tools, is related to their use. The data present technical difficulties for the practitioner, such as the presence of mixed mode data, missing data and errors in variables. These complications are overcome by employing a finite mixture model and Markov chain Monte Carlo methods. The analysis uses prior information which expresses the archaeologist’s belief that there are two tool groups that are similar to contemporary adzes and axes. The resulting mixing densities provide evidence that the morphological dimensional variability among tools is related to the existence of these two tool groups.
Modelling Variability in the Branching Structure of Strawberry Inflorescences
Authors: Ridout Martin S. , Morgan Byron J. T. , Taylor David R.
Published: March 2003

The branching structure of inflorescences of the cultivated strawberry (Fragaria×ananassa Duch.) is very variable. This paper demonstrates that some aspects of this variability are well described by a simple stochastic model of branching that has two adjustable parameters. The model is shown to provide a good fit to data from a set of almost 700 inflorescences of the cultivar Elsanta, collected over two successive years. For one parameter the maximum likelihood estimator is a moment estimator which is fully efficient even if the detailed branching structure of the inflorescences is not recorded. This parameter provides a convenient summary of branching vigour. The maximum likelihood estimator of the second parameter must be determined iteratively and can be quite inefficient unless the full branching structure is recorded. The model demonstrates that branching structure is affected by the order in which inflorescences emerge on the plant.
The Multivariate Gaussian Tail Model: An Application to Oceanographic Data
Authors: Bortot Paola , Coles Stuart , Tawn Jonathan
Published: March 2003

Optimal design of sea-walls requires the extreme value analysis of a variety of oceanographic data. Asymptotic arguments suggest the use of multivariate extreme value models, but empirical studies based on data from several UK locations have revealed an inadequacy of this class for modelling the types of dependence that are often encountered in such data. This paper develops a specific model based on the marginal transformation of the tail of a multivariate Gaussian distribution and examines its utility in overcoming the limitations that are encountered with the current methodology. Diagnostics for the model are developed and the robustness of the model is demonstrated through a simulation study. Our analysis focuses on extreme sea-levels at Newlyn, a port in south-west England, for which previous studies had given conflicting estimates of the probability of flooding. The novel diagnostics suggest that this discrepancy may be due to the weak dependence at extreme levels between wave periods and both wave heights and still water levels. The multivariate Gaussian tail model is shown to resolve the conflict and to offer a convincing description of the extremal sea-state process at Newlyn.
A Bayesian Analysis of Fluid Flow in Pipe-Lines
Authors: Rougier Jonathan , Goldstein Michael
Published: March 2003

The waterhammer equations are a pair of partial differential equations that describe the behaviour of an incompressible fluid in a pipe-line. We generalize these equations to account for uncertainty in the description of the liquid and the pipe-line, the behaviour of the boundaries of the pipe-line and the method of solution. We illustrate applications of our model to pipe-line design and to realtime pipe-line monitoring, e.g. for detecting leaks, and discuss the general features of our approach to the careful sourcing of uncertainty in deterministic models.
Multivariate modelling of the autoregressive random variance process
Authors: So Mike K. P. , Li W. K. , Lam K.
Published: March 2003

The autoregressive random variance (ARV) model proposed by Taylor (Financial returns modelled by the product of two stochastic processes, a study of daily sugar prices 1961–79. In Time Series Analysis: Theory and Practice 1 (ed. O. D. Anderson). Amsterdam: North‐Holland, 1982, pp. 203–26) is useful in modelling stochastic changes in the variance structure of a time series. In this paper we focus on a general multivariate ARV model. A traditional EM algorithm is derived as the estimation method. The proposed EM approach is simple to program, computationally efficient and numerically well behaved. The asymptotic variance‐‐covariance matrix can be easily computed as a by‐product using a well‐kno wn asymptotic result for extremum estimators. A result that is of interest in itself is that the dimension of the augmented state space form used in computing the variance–covariance matrix can be shown to be greatly reduced, resulting in greater computational efficiency . The multivariate ARV model considered here is useful in studying the lead–lag (causality) relationship of the variance structure across different time series. As an example, the leading effect of Thailand on Malaysia in terms of vari ance changes in the stock indices is demonstrated.
Iterative Least Squares Estimation and Identification of the Transfer Function Model
Authors: Muller Daniel , Wei William W. S.
Published: March 2003

The ordinary least squares method is the most commonly used estimation procedure in statistics but estimates of the input and output parameters through this method for transfer function models are not necessarily consistent. An iterative regression procedure is proposed to produce consistent estimates. Consistent moment estimates are also given. On the basis of these consistent estimates a method of model specification is proposed. An example is given to illustrate the procedure
Testing for Unit Roots in Monthly Time Series
Authors: Taylor A. M. Robert
Published: March 2003

This paper is concerned with tests for seasonal roots in monthly univariate time series processes. The paper extends the procedures and tables of critical values due to Beaulieu and Miron (Seasonal unit roots in aggregate U.S. data. J. Economet. 55 (1993), 305–28) to obtain tests which are similar ( exactly and a symptotically) with respect to both the initial values of the process and the possibility of seasonal drifts under the seasonal unit root null hypothesis. We also develop test statistics which test simultaneously for a unit root at each frequency and for a unit root at each of the seasonal frequencies. Representations are derived for the limiting distributions of each of the test statistics proposed in this paper. We illustrate the practical usefulness of the proposed test statistics by a series of empirical applications
Testing for a Structural Break at Unknown Date with Long‐memory Disturbances
Authors: Wright Jonathan H.
Published: March 2003

We derive the null limiting distributions of the usual sup‐Wald and CUSUM tests for structural stability with an unknown potential break date in a polynomial regressi on model where the errors are I(d), −0.5 < d < 0.5. For d > 0, both tests diverge under the null so that the asymptotic size of either test is unity. For d< 0, both tests converge to zero under the null so that the asymptotic size of either test is zero
Goodness‐of‐fit Test in Parametric Time Series Models
Authors: Prewitt Kathryn
Published: March 2003

A goodness‐of‐fit test is proposed which uses nonparametric curve estimation methods to investigate the fit of parametric models for the spectral density. A test of the null hypothesis that the function has parametric form is considered with a test statistic which compares parametric estimates and nonparametric kernel estimates of the function and its derivatives at a preselected number of points. An important issue for the nonparametric estimator is bandwidth choice, and we propose a data‐adaptive method for local bandwidth choice. Under the null hypothesis, asymptotically the test statistic has a χ2 distribution. Some practical issues are discussed.
Seasonal Moving‐average Unit Root Tests in the Presence of a Linear Trend
Authors: Tam Wing‐kuen , Reinsel Gregory
Published: March 2003

To distinguish stochastic from deterministic seasonality, test procedures are developed for a unit root in the integrated seasonal moving‐average (SMA) model when an underlying deterministic trend is present. Locally best invariant unbiase (LBIU) and point optimal invariant tests are considered. Their asymptotic distributions are developed and are found to differ from those for the no‐linear‐trend case. The limiting distribution of the LBIU statistic is expressed as a functional of Brownian motions. The procedures are extended to more general seasonal autoregressive moving‐average (ARMA) models, and to the inclusion of exogenous regressors. Finite‐sample distributions are also derived for the SMA(1) model. Simulations suggest that these distributions provide accurate approximations for more general ARMA models. A numerical example is included to illustrate the tests.