bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Detection of Influential Subsets in Linear Regression by Using an Influence Matrix
Authors: Peña Daniel , Yohai Victor J. 
Published: December 2018

SUMMARY
This paper presents a new method to identify influential subsets in linear regression problems. The procedure uses the eigenstructure of an influence matrix which is defined as the matrix of uncentred covariances of the effect on the whole data set of deleting each observation, normalized to include the univariate Cook statistics on the diagonal. It is shown that the eigenstructure of the influence matrix is useful to identify influential subsets and a procedure for detecting influential sets is proposed. The method is illustrated with two examples.
Deletion Influence and Masking in Regression
Authors: Lawrance A. J. 
Published: December 2018

SUMMARY
The paper is concerned with masking of Cook's distance, the popular deletion measure of influence of individual data cases in linear regression. Masking is broadly concerned with the limitations imposed by the use of individual cases. Two specific views are drawn from quotations: the first is associated with the established idea of joint influence, i.e. the deletion of two or more cases simultaneously, and the second is conditional influence, i.e. the calculation of Cook's distance before and after the deletion of other cases. Attention is mainly focused on pairs of already identified cases. Intuitive understanding is obtained via explicit general forms for joint and conditional Cook's distance influence with pairs of cases; especially tractable results are obtained for replicate and opposite explanatory pairs, and for multiples of individual cases of opposite pairs. The noteworthy effects possible in joint influence are described as reducing, enhancing and swamping; in conditional influence, interesting effects are described as masking and boosting. Thus only in connection with one effect in conditional influence is the term masking used. The work is illustrated on one constructed and one reported data set.
A Method for Generating and Labelling All Regular Fractions or Blocks for QN – M-Designs
Authors: Laycock P. J. , Rowley P. J. 
Published: December 2018

SUMMARY
By exploiting the vector space structure of regular qn – m-designs we construct and demonstrate a method for generating all such designs, without repetition, along with their confounded interactions, resolution numbers, alias sets and a decodable design number.
Wavelet Shrinkage: Asymptopia?
Authors: Donoho David L. , Johnstone Iain M. , Kerkyacharian Gérard , Picard Dominique 
Published: December 2018

SUMMARY
Much recent effort has sought asymptotically minimax methods for recovering infinite dimensional objects—curves, densities, spectral densities, images—from noisy data. A now rich and complex body of work develops nearly or exactly minimax estimators for an array of interesting problems. Unfortunately, the results have rarely moved into practice, for a variety of reasons—among them being similarity to known methods, computational intractability and lack of spatial adaptivity. We discuss a method for curve estimation based on n noisy data: translate the empirical wavelet coefficients towards the origin by an amount √(2 log n)σ/√n. The proposal differs from those in current use, is computationally practical and is spatially adaptive; it thus avoids several of the previous objections. Further, the method is nearly minimax both for a wide variety of loss functions—pointwise error, global error measured in Lp-norms, pointwise and global error in estimation of derivatives—and for a wide range of smoothness classes, including standard Holder and Sobolev classes, and bounded variation. This is a much broader near optimality than anything previously proposed: we draw loose parallels with near optimality in robustness and also with the broad near eigenfunction properties of wavelets themselves. Finally, the theory underlying the method is interesting, as it exploits a correspondence between statistical questions and questions of optimal recovery and information-based complexity.
Data-Driven Bandwidth Selection in Local Polynomial Fitting: Variable Bandwidth and Spatial Adaptation
Authors: Fan Jianqing , Gijbels Irene 
Published: December 2018

SUMMARY
When estimating a mean regression function and its derivatives, locally weighted least squares regression has proven to be a very attractive technique. The present paper focuses on the important issue of how to select the smoothing parameter or bandwidth. In the case of estimating curves with a complicated structure, a variable bandwidth is desirable. Furthermore, the bandwidth should be indicated by the data themselves. Recent developments in nonparametric smoothing techniques inspired us to propose such a data-driven bandwidth selection procedure, which can be used to select both constant and variable bandwidths. The idea is based on a residual squares criterion along with a good approximation of the bias and variance of the estimator. The procedure can be applied to select bandwidths not only for estimating the regression curve but also for estimating its derivatives. The resulting estimation procedure has the necessary flexibility for capturing complicated shapes of curves. This is illustrated via a large variety of testing examples, including examples with a large spatial variability. The results are also compared with wavelet thresholding techniques, and it seems that our results are at least comparable, i.e. local polynomial regression using our data-driven variable bandwidth has spatial adaptation properties that are similar to wavelets.
Properties of Invariant Distributions and Lyapunov Exponents for Chaotic Logistic Maps
Authors: Hall Peter , Wolff Rodney C. L. 
Published: December 2018

SUMMARY
Statistical scientists have recently focused sharp attention on properties of iterated chaotic maps, with a view to employing such processes to model naturally occurring phenomena. In the present paper we treat the logistic map, which has earlier been studied in the context of modelling biological systems. We derive theory describing properties of ‘invariant’ or ‘stationary’ distributions under logistic maps and apply those results in conjunction with numerical work to develop further properties of invariant distributions and Lyapunov exponents. We describe the role that poles play in determining properties of densities of iterated distributions and show how poles arise from iterated mappings of the centre of the interval to which the map is applied. Particular attention is paid to the shape of an invariant distribution in the tails or in the neighbourhood of a pole of its density. A new technique is developed for this application. It enables us to combine ‘parametric’ information, available from the structure of the map, with ‘nonparametric’ information obtainable from numerical experiments.
Multivariate Logistic Models
Authors: Glonek G. F. V. , McCullagh P. 
Published: December 2018

SUMMARY
When data composed of several categorical responses together with categorical or continuous predictors are observed, the multivariate logistic transform introduced by McCullagh and Nelder can be used to define a class of regression models that is, in many applications, particularly suitable for relating the joint distribution of the responses to predictors. In this paper we give a general definition of this class of models and study their properties. A computational scheme for performing maximum likelihood estimation for data sets of moderate size is described and a system of model formulae that succinctly define particular models is introduced. Applications of these models to longitudinal problems are illustrated by numerical examples.
Response Surface Bandits
Authors: Ginebra Josep , Clayton Murray K. 
Published: December 2018

SUMMARY
In this paper we define a response surface bandit as the sequential design problem that maximizes an expected bandit utility but where the outcomes yn are continuous and can be related through a response surface to a set of controllable variables xn = (x 1n, x 2n,···, xkn). We link this problem to other traditional optimization problems from industrial engineering and to the traditional bandit problem. We consider two approaches to the problem. The first is based on a myopic sequential design. The second approach uses the best design out of a family of designs related to upper bounds for the predicted surface; the family includes myopic and sequential versions of D-optimal designs. These approaches can be generalized to more broadly defined sequential problems.
Report of the Editors—1995
Authors: Atkinson A. C. , Young G. A. 
Published: December 2018

Abstract
We have two Joint Editors and a panel of around 16 Associate Editors, each of whom customarily serves for four years so, as usual, there have been several changes in the editorial arrangements over the last year. Anthony Atkinson retires as Joint Editor at the end of December 1995 and will be replaced by Chris Jones (The Open University). The new Associate Editors are Ray Chambers (University of Southampton), John Copas (University of Warwick), David Draper (University of Bath) and David Madigan (University of Washington). In addition Trevor Sweeting has agreed to continue beyond his original four-year term. The retiring Associate Editors are John Haslett, Tony Lawrance, Roger Sugden and Luke Tierney. We take this opportunity to thank them and all the Associate Editors for their hard work for the journal.
A Simple and Accurate Method for Approximate Conditional Inference Applied to Exponential Family Models
Authors: Waterman Richard P. , Lindsay Bruce G. 
Published: December 2018

SUMMARY
A simple method for approximate conditional inference is described. The methodology is applied to natural exponential family models where it is shown to provide accurate approximations to fully conditional estimates. The approximation technique can be applied much more generally than in this particular class of models. The technique depends only on the construction of certain 'projected scores' derived from higher order likelihood derivatives and their covariances and so can be used in many problems where it is relevant to control for the estimation of nuisance parameters.
Accounting for Covariates Observed Post Randomization for Discrete and Continuous Repeated Measures Data
Authors: Rochon James 
Published: December 2018

SUMMARY
Adjusting for covariates observed post randomization is a difficult issue in randomized clinical trials. One approach is to enter these covariates as time-dependent covariates in a general linear model. However, this approach fails to account for interactions between the primary end point and confounding variable as they evolve over time. In this paper, we adopt the view that, since the confounder is observed following randomization, it should be treated as an outcome and analysed accordingly. We consider the repeated measures design where both the primary end point and the confounding measure are observed repeatedly over patient follow-up. A generalized estimating equation model is applied to allow each set of repeated measures to be modelled in terms of important explanatory variables. Seemingly unrelated regression combines the two models into an overall framework for analysis. Inference is then performed by imposing restrictions on the confounder regression parameters to reflect the behaviour profile of interest. Estimation and identification procedures are described and the methodology is illustrated with an example.
Bayes Linear Sufficiency and Systems of Expert Posterior Assessments
Authors: Goldstein M. , O'Hagan A. 
Published: December 2018

SUMMARY
Data arising in the form of expert assessments are received by a decision maker. The decision maker is required to estimate a set of unknown quantities, and receives expert assessments at varying levels of accuracy, on samples of the quantities of interest. We present a Bayes linear analysis of this problem. In the absence of other assessments, the decision maker will accept as his or her current estimate of any single quantity the most accurate received assessment of that quantity. This leads to a sufficiency property which allows a simple decomposition of the error structure of assessments. Bayes linear estimation is then used by the decision maker to estimate each quantity of interest given an arbitrary collection of received assessments. The analysis is motivated throughout by a practical context in which a large company needs to estimate costs for renovation of assets. The methodology is illustrated with a numerical example.
Monte Carlo Exact Conditional Tests for Log-Linear and Logistic Models
Authors: Forster Jonathan J. , McDonald John W. , Smith Peter W. F. 
Published: December 2018

SUMMARY
The form of the exact conditional distribution of a sufficient statistic for the interest parameters, given a sufficient statistic for the nuisance parameters, is derived for a generalized linear model with canonical link. General results for log-linear and logistic models are given. A Gibbs sampling approach for generating from the conditional distribution is proposed, which enables Monte Carlo exact conditional tests to be performed. Examples include tests for goodness of fit of the all-two-way interaction model for a 28-table and of a simple logistic model. Tests against non-saturated alternatives are also considered.
Wavelet Shrinkage Using Cross-Validation
Authors: Nason G. P. 
Published: December 2018

SUMMARY
Wavelets are orthonormal basis functions with special properties that show potential in many areas of mathematics and statistics. This paper concentrates on the estimation of functions and images from noisy data by using wavelet shrinkage. A modified form of twofold cross-validation is introduced to choose a threshold for wavelet shrinkage estimators operating on data sets of length a power of 2. The cross-validation algorithm is then extended to data sets of any length and to multidimensional data sets. The algorithms are compared with established threshold choosers by using simulation. An application to a real data set arising from anaesthesia is presented.
Regression with Doubly Censored Current Status Data
Authors: Rabinowitz Daniel , Jewell Nicholas P. 
Published: December 2018

SUMMARY
Data from settings in which an initiating event and a subsequent event occur in sequence are called doubly censored current status data if the time of neither event is observed directly, but instead it is determined at a random monitoring time whether either the initiating or subsequent event has yet occurred. This paper is concerned with using doubly censored current status data to estimate the regression coefficient in an accelerated failure time model for the length of time between the initiating event and the subsequent event. Motivated by a problem in the epidemiology of acquired immune deficiency syndrome, attention here is focused on a special case, the case in which the initiating event, given that it has occurred before the monitoring time, may be assumed to follow a uniform distribution. The main result is that the likelihood in the special case has the same structure as the likelihood in a simpler setting, the setting in which the time of the initiating event is known. The result allows methods developed for the simpler setting to be applied in the special case. The results of the application of the approach to real data are reported.
On Pseudodata Methods for Removing Boundary Effects in Kernel Density Estimation
Authors: Cowling Ann , Hall Peter 
Published: December 2018

SUMMARY
We suggest a method for boundary correcting kernel density estimators, based on generating pseudodata beyond the extremities of the density's support. The estimator produced in this way enjoys optimal orders of bias and variance right up to the ends of the support, and it may be used with kernels of arbitrary order. Our method is considerably more adaptive than the common data reflection approach, which is not really appropriate for kernels of order 2 or more since it does not adequately correct boundary bias. In a simulation study, for densities on [0,1] with positive slope at x = 0, our method was found to have lower mean-squared error at x = 0 than the boundary kernel method, especially for small sample sizes. Our technique may be used in conjunction with plug-in or least squares cross-validation methods of bandwidth selection and has an analogue in the context of estimating a point process intensity.
Measuring Discordancy between Prior and Data
Authors: Young K. D. S. , Pettit L. I. 
Published: December 2018

SUMMARY
In this paper we consider possible measures of the degree of discordancy between a proper prior and observed data. A consideration of the problem when we gain complete knowledge of the parameters suggests that measures based on tail areas are unsuitable. A wish for invariance under transformations leads to a Bayes factor comparing the marginal distribution of the data with the proper prior with that with a non-informative prior. to overcome problems with improper priors some suggestions are compared. A measure based on a fractional Bayes factor is preferred. The method is illustrated for normal samples, binomial samples and linear models.
Sexually dimorphic gene expression and transcriptome evolution provide mixed evidence for a fast‐Z effect in Heliconius
Authors: Pinharanda Ana , Rousselle Marjolaine , Martin Simon H. , Hanly Joe J. , Davey John W. , Kumar Sujai , Galtier Nicolas , Jiggins Chris D. 
Published: December 2018

AbstractSex chromosomes have different evolutionary properties compared to autosomes due to their hemizygous nature. In particular, recessive mutations are more readily exposed to selection, which can lead to faster rates of molecular evolution. Here, we report patterns of gene expression and molecular evolution for a group of butterflies. First, we improve the completeness of the Heliconius melpomene reference annotation, a neotropical butterfly with a ZW sex determination system. Then, we analyse RNA from male and female whole abdomens and sequence female ovary and gut tissue to identify sex‐ and tissue‐specific gene expression profiles in H. melpomene. Using these expression profiles, we compare (a) sequence divergence and polymorphism; (b) the strength of positive and negative selection; and (c) rates of adaptive evolution, for Z and autosomal genes between two species of Heliconius butterflies, H. melpomene and H. erato. We show that the rate of adaptive substitutions is higher for Z than autosomal genes, but contrary to expectation, it is also higher for male‐biased than female‐biased genes. Additionally, we find no significant increase in the rate of adaptive evolution or purifying selection on genes expressed in ovary tissue, a heterogametic‐specific tissue. Our results contribute to a growing body of literature from other ZW systems that also provide mixed evidence for a fast‐Z effect where hemizygosity influences the rate of adaptive substitutions.
Cytogenetic Biomonitoring of Dental Technicians: A Cross‐Sectional Study
Authors: Tadin Antonija , Gavic Lidia , Jurkovic Ivana , Vidovic Neven , Jerkovic Daniel , Zeljezic Davor 
Published: December 2018

AbstractPurposeThis is a cross‐sectional study to assess the incidence of micronuclei and other nuclear morphological changes in buccal epithelial cells of dental technicians.Materials and MethodsThe study was conducted on 45 dental technicians versus 2 control groups: 50 dentists and 50 dental assistants. DNA damage was analyzed in exfoliated buccal mucosa cells by micronucleus assay. The differences in the frequency of detected types of cytogenetic damage between experimental groups were analyzed by applying 2‐way ANOVA with Tukey's HSD post‐hoc test.ResultsDentists and dental assistants have significantly lower incidence of micronucleated cells than technicians (mean ± SD: 0.68 ± 0.74, 0.58 ± 0.81, and 1.58 ± 2.07; p = 0.031 and p = 0.015, respectively), and this trend also holds for karyolitic cells (0.10 ± 0.30, 0.20 ± 0.49, and 1.42 ± 1.25; p < 0.001 and p < 0.001, respectively), condensed chromatin (0.16 ± 0.37, 0.14 ± 0.35, and 0.76 ± 0.98; p < 0.001 and p < 0.001, respectively), and pyknotic cells (0.04 ± 0.20, 0.08 ± 0.27, and 0.96 ± 1.24; p < 0.001 and p < 0.001, respectively).ConclusionCytogenetic biomarkers in dental technician buccal mucosa are increased compared with control groups. This increase may be associated with more extensive exposure to potentially harmful components of the materials used in everyday dental practice.
When “Scurry” vs. “Hurry” Makes the Difference: Vermin Metaphors, Disgust, and Anti‐Immigrant Attitudes
Authors: Marshall Shantal R. , Shapiro Jenessa R. 
Published: December 2018

AbstractIn three studies, we demonstrate that common metaphors used to describe immigrants in news media interact with national, but not political, identity to lead to feelings of disgust as well as anti‐immigrant attitudes. The first study demonstrates that the current discourse in the U.S. surrounding unauthorized immigrants includes metaphors that readily activate thoughts of vermin (e.g., rodents). The second study shows that when these metaphors are present in a news article about immigrants, the more participants identify as American the more disgust they experience reading the article. The final study further shows that after reading a news article in which the vermin metaphors are present, the more participants identify as American the more likely they are to support stringent immigration policies. This research shows the power of metaphor to shape intergroup attitudes and support for government policies.
Anaphylaxis management in Australian schools: Review of guidelines and adrenaline autoinjector use
Authors: Vale Sandra , Netting Merryn J , Ford Lara S , Tyquin Briony , McWilliam Vicki , Campbell Dianne E 
Published: December 2018

AbstractFood allergy and anaphylaxis is increasing in Australian children, and anaphylaxis is relatively common in Australian schools. This review aims to provide an overview of current policies and practices for anaphylaxis management in Australian schools, including approaches to risk mitigation and anaphylaxis training. We reviewed literature related to anaphylaxis training in the school setting published between 2010 and 2018. Current anaphylaxis policies/guidelines were obtained from Australian education and health departments, and reports of suspected anaphylaxis and adrenaline autoinjector (AAI) use for 2016–2017 were obtained from education departments where available. Our review of policies/guidelines across Australian jurisdictions indicates inconsistent approaches to anaphylaxis management training. Almost half of Australian school anaphylaxis events required a general‐use AAI, administered to students not identified as at risk of anaphylaxis. Development of clear, evidence‐based, consistent guidelines related to anaphylaxis management and training in the school setting is imperative to minimise risk.