bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bounded Influence Rank Regression
Authors: Naranjo J. D. , Hettmansperger T. P. 
Published: December 2018

SUMMARY
When εi = yi – x′i β, it is known that minimizing ΣΣ|εi – εj| yields an estimate of regression that attains a bounded influence of the residual with 95% efficiency for the normal distribution. We show that introducing weights ΣΣbij|εi – εj| achieves bounded total influence with positive breakdown. Mallows weights in particular are optimally efficient under a predefined bound on the gross error sensitivity. A generalization of Mallows weights allows additional local stability against high leverage points. Two numerical examples illustrate the behaviour of the estimate.
A Note on Noisy Chaos
Authors: Chan K. S. , Tong H. 
Published: December 2018

SUMMARY
We prove that, under appropriate conditions, in a noisy environment an embedded deterministic dynamical system which admits a compact attractor can give rise to an ergodic stochastic system. This observation justifies the stochastic set-up in the study of deterministic chaos. We also clarify a folklore concerning polynomial autoregression.
Estimation of Finite Mixture Distributions Through Bayesian Sampling
Authors: Diebolt Jean , Robert Christian P. 
Published: December 2018

SUMMARY
A formal Bayesian analysis of a mixture model usually leads to intractable calculations, since the posterior distribution takes into account all the partitions of the sample. We present approximation methods which evaluate the posterior distribution and Bayes estimators by Gibbs sampling, relying on the missing data structure of the mixture model. The data augmentation method is shown to converge geometrically, since a duality principle transfers properties from the discrete missing data chain to the parameters. The fully conditional Gibbs alternative is shown to be ergodic and geometric convergence is established in the normal case. We also consider non-informative approximations associated with improper priors, assuming that the sample corresponds exactly to a k-component mixture.
Mixture Designs for Q Components in Orthogonal Blocks
Authors: Lewis S. M. , Draper N. R. , Dean A. M. , Prescott P. 
Published: December 2018

SUMMARY
In industrial experimentation designs are needed to estimate the effects of mixture components independently of process variables. This paper gives general methods of constructing designs for q ≥ 3 mixture components in two or more orthogonal blocks. The designs are built from Latin squares with specific properties and are generalizations of those for four and five components given by Draper and co-workers and Prescott and co-workers respectively.
Reinforced Lattices
Authors: Pearce S. C. 
Published: December 2018

SUMMARY
Reinforcement is here meant the addition of plots of standard treatments to the blocks of a non-orthogonal design to improve it. The purpose could be either to aid a comparison of the existing treatments or to facilitate their comparison with the standards. The position is examined for both square and rectangular lattices in block designs and for rectangular lattices in row-and-column designs. It is concluded that the method could be useful in practice.
The Inadmissibility of Certain Bayes Decision Rules Under Vague Priors in Location Problems
Authors: Smith J. Q. 
Published: December 2018

SUMMARY
It is shown that, when improper, translation invariant priors distributions are used in the Bayesian analysis of a single location parameter, the related Bayes decision rules associated with a wide class of loss functions are inadmissible. It is concluded that the routine use of improper distributions, even in translation problems, can be misleading.
Fractional Bayes Factors for Model Comparison
Authors: O'Hagan Anthony 
Published: December 2018

SUMMARY
Bayesian comparison of models is achieved simply by calculation of posterior probabilities of the models themselves. However, there are difficulties with this approach when prior information about the parameters of the various models is weak. Partial Bayes factors offer a resolution of the problem by setting aside part of the data as a training sample. The training sample is used to obtain an initial informative posterior distribution of the parameters in each model. Model comparison is then based on a Bayes factor calculated from the remaining data. Properties of partial Bayes factors are discussed, particularly in the context of weak prior information, and they are found to have advantages over other proposed methods of model comparison. A new variant of the partial Bayes factor, the fractional Bayes factor, is advocated on grounds of consistency, simplicity, robustness and coherence.
Majorization and D-Optimality for Complete Block Designs Under Correlations
Authors: Bhaumik Dulal K. 
Published: December 2018

SUMMARY
D-optimal designs are derived in the complete block design set-up for comparing treatments using ordinary least squares estimators when the experimental errors are correlated. It is shown that the D-optimal design is different from the weakly universally optimal design of Morgan and Chakravarti, and Kiefer and Wynn.
Bayesian Model Choice Via Markov Chain Monte Carlo Methods
Authors: Carlin Bradley P. , Chib Siddhartha 
Published: December 2018

SUMMARY
Markov chain Monte Carlo (MCMC) integration methods enable the fitting of models of virtually unlimited complexity, and as such have revolutionized the practice of Bayesian data analysis. However, comparison across models may not proceed in a completely analogous fashion, owing to violations of the conditions sufficient to ensure convergence of the Markov chain. In this paper we present a framework for Bayesian model choice, along with an MCMC algorithm that does not suffer from convergence difficulties. Our algorithm applies equally well to problems where only one model is contemplated but its proper size is not known at the outset, such as problems involving integer-valued parameters, multiple changepoints or finite mixture distributions. We illustrate our approach with two published examples.
Nonparametric Transformations for Both Sides of a Regression Model
Authors: Nychka Douglas , Ruppert David 
Published: December 2018

SUMMARY
One way to model heteroscedasticity and skewness of the error distribution in regression is to transform both sides of the regression equation. If it is possible to transform the regression equation to result in normally distributed errors, then we can obtain more efficient parameter estimates and valid prediction intervals. One problem with this approach is that the choice of transformation is usually restricted to the power or shifted power family. Often there is no scientific basis for this model and the limited flexibility of this parametric family may miss important features of the distribution. A more comprehensive approach is to estimate the transformation by using nonparametric methods based on maximizing a penalized likelihood function. This maximization problem leads naturally to a spline estimate for the log-derivative of the transformation. An algorithm for computing the estimate is given along with results on the existence and uniqueness of the estimate. This nonparametric method is illustrated by using a non-normally distributed fisheries data set.
Incorporating Parametric Effects into Functional Principal Components Analysis
Authors: Silverman B. W. 
Published: December 2018

SUMMARY
The ideas of functional principal component analysis are extended to deal with data that are hybrids of ‘functional’ and ‘parametric’ effects. The parametric effects may be more general than just the addition of a multiple of a given function. A detailed development is given in the case of shifts of the time axis for functions observed on a periodic interval, and some remarks are made for the extension to a far more general case. Given data, a Procrustes fitting method can be used to estimate the parametric effects. Several possible ways of treating the estimated parameter values are discussed. The methods are illustrated by reference to temperature data at 35 Canadian weather-stations.
The Exact and Asymptotic Distributions of Cramér-Von Mises Statistics
Authors: CSöRgő Sándor , Faraway Julian J. 
Published: December 2018

SUMMARY
It is shown that an asymptotically precise one-term correction to the asymptotic distribution function of the classical Cramér-von Mises statistic approximates the exact distribution function remarkably closely for sample sizes as small as 7 or even smaller. This correction can be quickly evaluated, and hence it is suitable for the computation of practically exact p-values when testing simple goodness of fit. Similar findings hold for Watson's rotationally invariant modification, where a sample size of 4 appears to suffice.
Quasi-Linear Bayes Estimation in Stratified Finite Populations
Authors: Cocchi Daniela , Mouchart Michel 
Published: December 2018

SUMMARY
In this paper a Bayesian least squares approximation is proposed for descriptive inference in a finite population when a categorical auxiliary variable is known. A hierarchical model II analysis of variance is assumed. The solution consists of a projection on the vector of group totals and on the between and within sums of squares. The approximation can be seen as a normal approximation of the joint distribution of the statistic and of the parameter of interest, conditional on two discrete variables: these denote attribution to one group and selection in the sample. The main consequence of the conditioning is that conjectures about non-normality can be taken into account. The solution is compared with others that have been published.
Variance Estimation for Statistics Computed from Spatial Lattice Data
Authors: Sherman Michael 
Published: December 2018

SUMMARY
A statistic s() is computed on spatially indexed data {X i: i ∈ D), where D is a finite subset of the integer lattice Z2. We propose a method for estimating the variance (and other moments) of s() by using only the data. The set D may be irregularly shaped, the statistic s() may be arbitrarily complicated and no distributional assumptions (marginal or joint) are necessary. The method uses the statistic computed on overlapping 'subshapes' of D as replicates of s(). The estimator is simply the sample variance of the (standardized) replicates. We demonstrate L 2-consistency of the estimator (under mild conditions on s() and the strength of spatial dependence). A rate of convergence is also given, giving guidance into the appropriate choice of subshape size, and the estimator is illustrated in two data examples.
Asymptotic Efficiency of the Sample Mean in Markov Chain Monte Carlo Schemes
Authors: Yue Huibin , Chan K. S. 
Published: December 2018

SUMMARY
In many cases, a univariate time series derived from a time reversible stationary Markov chain has the property that there is a distribution function on [–1, 1] ([0, 1]) such that, for all non-negative integers l, its lth moment is the lth lag autocorrelation of the time series. We discuss some consequences of this property. Effects of the asymptotic efficiency of the sample mean on the efficiency of subsampling a stationary Markov chain are discussed. The stationarity assumption is then relaxed. We show that under certain regularity conditions the sample mean of a strongly asymptotically stationary process is asymptotically efficient in that it has the smallest mean-square error asymptotically in a broad class of linear estimators.
Continuum Regression is Not Always Continuous
Authors: Björkström Anders , Sundberg Rolf 
Published: December 2018

SUMMARY
Continuum regression (CR) is regression of a response y on that linear combination t γ of explanatory variables which maximizes r 2(y, t) var(t)γ, where γ is chosen from a continuum of candidates. CR includes several common methods as special cases: ordinary least squares, principal component regression, partial least squares and a modified ridge regression. We demonstrate that CR, despite its name, can yield a predictor that is a discontinuous function of γ and of the calibration data. We illustrate this with a set of real data. The relationship between CR and ridge regression is the key to understanding this phenomenon.
On the Asymptotic Behaviour of the Pseudolikelihood Ratio Test Statistic
Authors: Liang Kung-Yee , Self Steven G. 
Published: December 2018

SUMMARY
This paper concerns the asymptotic distribution of the likelihood ratio statistic T for testing H 0: θ = θ 0 based on the pseudolikelihood L(θ,ϕ^), where ϕ^ is a simple estimator of ϕ. We show that the asymptotic distribution of T under H 0 is a weighted sum of independent χ 1 2-variables where the weights involve the asymptotic joint covariance matrix of ϕ^ and the score function for θ. Some sufficient conditions are provided for the limiting distribution to be χ 2. The result is extended to allow θ 0 to be a boundary value of the θ parameter space, and ϕ to be misspecified in L(θ, ϕ). We also examine the issue of power loss when ϕ is misspecified in L(θ, ϕ). Several examples including variance component models, multivariate survival models, genetic linkage analysis and the Behrens–Fisher problem are presented to demonstrate the scope of the problems considered and to illustrate the results.
Eclipsing Atlantis: Trans‐Atlantic Multilateralism in Trade and Monetary Affairs as a Pre‐History to the Genesis of Social Market Europe (1942–1950)
Authors: Segers Mathieu 
Published: December 2018

AbstractThe common understanding of the history of European integration obfuscates much of the strong bonds between European integration and its pre‐history in western multilateral co‐operation This western co‐operation centred around the inter‐connected policy fields of monetary management, trade and social policies during the pre‐phase of European integration. This contribution reconstructs the trans‐Atlantic institutional framework, within which a unique multilateralism in post‐war Western Europe, could emerge. The analysis suggests new explanations for the specific design, which characterizes this European variant of post‐war multilateralism: a regionally oriented ‘social market’ pursued through a process of European integration.
New active package based on titania coated on cardboard for storage of fresh prepared orange juice
Authors: Peter Anca , Nicula Camelia , Mihaly‐Cozmuta Leonard , Mihaly‐Cozmuta Anca 
Published: December 2018

AbstractAn active package from cardboard coated with titanium dioxide was designed for storage of fresh prepared orange juice. The organoleptical changes of the orange juice were statistically significant and revealed the preservation role of the active cardboard at 4 °C. Statistically significant positive effect on the reducing the rate of ascorbic acid degradation and on the increasing the catalase activity, respectively, was generated by coating TiO2, revealing that the semiconductor favors the preservation of the orange juice during storage. FTIR spectra revealed new compounds in the juice stored in the active package at 4 °C, but these substances has no significantly affected the characteristics of the juice. This study reveals that the TiO2‐cardboard is a promising solution to package fresh prepared orange juice and to store it in safety conditions at 4 °C for 7 days. The mechanism that ensure the preservation of juice as a result of TiO2 particles photoactivity was discussed.Practical applicationsThe study report about a new type of active package made from cardboard coated with TiO2 designed for storage of fresh prepared orange juice. The results showed the statistically significant and positive influence of TiO2 on preserving the organoleptical parameters, ascorbic acid content and catalase activity of the orange juice during storage for 9 days. This study reveals that the TiO2‐cardboard is a promising solution to package fresh prepared orange juice and to store it in safety conditions at 4 °C for 7 days.
A new anatomic approach of the ventricular septal defect in the interruption of the aortic arch
Authors: Mostefa Kara Meriem , Houyel Lucile , Bonnet Damien 
Published: December 2018

AbstractThe aim of this study was to analyse the anatomy of the ventricular septal defect (VSD) in heart specimens with interruption of the aortic arch (IAA) in order to explore the hypothesis of different embryologic mechanisms for the different anatomic types of IAA. We examined 42 human heart specimens, 25 with IAA as the main disease with concordant atrioventricular and ventriculo‐arterial connections and two distinct great arteries, and 17 hearts with IAA associated with other malformations [six common arterial trunk (CAT), five double‐outlet right ventricle (DORV), three transposition of the great arteries (TGA), three atrioventricular septal defect (AVSD)]. The interruption was classified according to Celoria and Patton. We focused on the anatomy of the VSD viewed from the right ventricular side. There were 15 IAA type A, 27 type B, no type C. The VSD in IAA type B was always an outlet VSD, located between the two limbs of the septal band, with posterior malalignment of the outlet septum in hearts with concordant ventriculo‐arterial connections, without any fibrous tricuspid‐aortic continuity. In addition, the aortic arch was always completely absent. Conversely, the VSD in IAA type A could be of any type (outlet in six, muscular in four, central perimembranous in two, inlet in three) and the aortic arch was either atretic or absent. In addition, IAA type B, when found in the setting of another anomaly, was always associated with neural crest‐related anomalies (CAT and DORV), whereas IAA type A was found in association with anomalies not related to the neural crest (TGA and AVSD). These results reinforce the hypothesis that different pathogenic mechanisms are responsible for the two types of IAA, and the inclusion of IAA type B in the group of neural crest defects. Conversely, IAA type A could be due to overlapping mechanisms: flow‐related defect (coarctation‐like) and neural crest contribution.
Abstractions on steroids: A critical realist approach to computer simulations
Authors: Törnberg Anton 
Published: December 2018

AbstractComputer simulations are increasingly used within various fields of the social sciences, including analytical sociology and computational social science. However, the method has yet to fully find its place within critical realism, generally regarded as reductionist and methodological individualist and thus inadequate to the task of grasping the full and enigmatic complexity of social life. This article contributes to the discussion by suggesting an alternative approach to computer simulations in the social realm. Instead of representing reality, simulations are seen as a way of boosting abstraction by enabling us to isolate and study the effects of emergent mechanisms. The need for such tools is growing more urgent in an age characterized by rapid change and global networks of causal interrelation. Hence there is a need not only for new tools to deal with causal complexity within critical realism, but also for a critical realist perspective to fill the meta‐theoretical vacuum on which the simulation approach is largely based. The approach developed here provides a challenge to the predominant ways in which simulations are utilized today, with increasingly sophisticated models aiming towards realistic representation on the basis of empirical data.
Evolution of tendon shape in an anuran clade and its relation to size, phylogeny and locomotion
Authors: Fratani J. , Ponssa M. L. , Abdala V. 
Published: December 2018

AbstractMost anatomical specializations related to anuran jumping have been observed in pelvic girdle and hindlimbs, which are characterized by its fused caudal vertebrae and elongated hindlimbs. Still, despite of a greatly specialized body plan, locomotor variation in anurans goes beyond jumping, including specializations for swimming, burrowing, and climbing. Herein, we test for morphological adaptation in three tendinous elements associated with the urostyle and hindlimb joints: the tendon of the longissimus dorsi which inserts on the urostyle and rotates it dorsally; the patellar tendon which goes over the knee joint and connects the larger thigh extensor muscles; and the Achilles tendon which passes over the ankle joint and participates in the catapult‐like mechanism of jumping species. We make an incursion in tendon variation using geometric morphometrics and test if tendon shape is related to size, phylogeny and locomotion in leptodactylid species. Also, we hypothesize that tarsal bone elongation in anura alters the heel into a more ‘knee‐like’ joint affecting tendon shape, and test for patellar and Achilles similarity. We found that a combination of factors drives Leptodactylidae tendon morphological diversity. Allometry, phylogeny and function take part in the longissimus dorsi tendon variation, with significant difference between hopping and all jumping species. The patellar tendon shape scales isometrically with size, with significant shape difference between jumping and jumping‐swimming species. Achilles tendon shape is mainly affected by allometry. Optimization showed a shift for a broader longissimus dorsi tendon shape in the ancestor of Leptodactylus. Finally, and contrary to our prediction, patellar and Achilles tendon shapes are significantly different. Once again, evidence points to a combination of factors explaining shape, rather than a direct and evident functional‐anatomic relation.
On hormonal regulation of the dynamic apical hook development
Authors: Wang Yichuan , Guo Hongwei 
Published: December 2018

SummaryTo deal with the ever‐changing environment, sessile plants adapt diverse and plastic organ structures during postembryonic development. Among these, the apical hook forms shortly after seed germination of most dicots, and protects the delicate shoot meristem from mechanical damage during soil emergence. For decades, this structure has been taken as an excellent model for the investigation of the mechanisms underlying the differential growth of plant tissues. Here, we summarize recent advances in the investigation of the hormonal regulation of apical hook development, focusing on the convergence to auxin and a central regulator HOOKLESS1 (HLS1). We propose the revisitation of hook curvature kinematics at suborgan and single‐cell resolution, and further pursuance of the mechanistics of apical hook development through combinatorial approaches of automated imaging and multidimensional modeling.
Homologous shell microstructures in Cambrian hyoliths and molluscs
Authors: Li Luoyang , Zhang Xingliang , Skovsted Christian B. , Yun Hao , Pan Bing , Li Guoxiang 
Published: December 2018

AbstractHyoliths were among the earliest biomineralizing metazoans in Palaeozoic marine environments. They have been known for two centuries and widely assigned to lophotrochozoans. However, their origin and relationships with modern lophotrochozoan clades have been a longstanding palaeontological controversy. Here, we provide broad microstructural data from hyolith conchs and opercula from the lower Cambrian Xinji Formation of North China, including two hyolithid genera and four orthothecid genera as well as unidentified opercula. Results show that most hyolith conchs contain a distinct aragonitic lamellar layer that is composed of foliated aragonite, except in the orthothecid New taxon 1 that has a crossed foliated lamellar microstructure. Opercula are mostly composed of foliated aragonite and occasionally foliated calcite. These blade or lath‐like microstructural fabrics coincide well with biomineralization of Cambrian molluscs rather than lophophorates, as exemplified by the Cambrian members of the tommotiid‐brachiopod linage. Accordingly, we propose that hyoliths and molluscs might have inherited their biomineralized skeletons from a non‐mineralized or weakly mineralized common ancestor rather than as a result of convergence. Consequently, from the view of biomineralization, the homologous shell microstructures in Cambrian hyoliths and molluscs strongly strengthen the phylogenetic links between the two groups.