Uniform Inference for Kernel Density Estimators with Dyadic Data

Dyadic data is often encountered when quantities of interest are associated with the edges of a network. As such it plays an important role in statistics, econometrics and many other data science disciplines. We consider the problem of uniformly estimating a dyadic Lebesgue density function, focusing on nonparametric kernel-based estimators taking the form of dyadic empirical processes. Our main contributions include the minimax-optimal uniform convergence rate of the dyadic kernel density estimator, along with strong approximation results for the associated standardized and Studentized $t$-processes. A consistent variance estimator enables the construction of valid and feasible uniform confidence bands for the unknown density function. We showcase the broad applicability of our results by developing novel counterfactual density estimation and inference methodology for dyadic data, which can be used for causal inference and program evaluation. A crucial feature of dyadic distributions is that they may be "degenerate" at certain points in the support of the data, a property making our analysis somewhat delicate. Nonetheless our methods for uniform inference remain robust to the potential presence of such points. For implementation purposes, we discuss inference procedures based on positive semi-definite covariance estimators, mean squared error optimal bandwidth selectors and robust bias correction techniques. We illustrate the empirical finite-sample performance of our methods both in simulations and with real-world trade data, for which we make comparisons between observed and counterfactual trade distributions in different years. Our technical results concerning strong approximations and maximal inequalities are of potential independent interest.Comment: Article: 23 pages, 3 figures. Supplemental appendix: 72 pages, 3 figure

Observations of the structure and evolution of solar flares with a soft X-ray telescope

Soft X ray flare events were observed with the S-056 X-ray telescope that was part of the ATM complement of instruments aboard SKYLAB. Analyses of these data are reported. The observations are summarized and a detailed discussion of the X-ray flare structures is presented. The data indicated that soft X-ray emitted by a flare come primarily from an intense well-defined core surrounded by a region of fainter, more diffuse emission. An analysis of flare evolution indicates evidence for preliminary heating and energy release prior to the main phase of the flare. Core features are found to be remarkably stable and retain their shape throughout a flare. Most changes in the overall configuration seem to be result of the appearance, disappearance or change in brightness of individual features, rather than the restructuring or reorientation of these features. Brief comparisons with several theories are presented

Yurinskii's Coupling for Martingales

Yurinskii's coupling is a popular theoretical tool for non-asymptotic distributional analysis in mathematical statistics and applied probability, offering a Gaussian strong approximation with an explicit error bound under easily verified conditions. Originally stated in $\ell^2$-norm for sums of independent random vectors, it has recently been extended both to the $\ell^p$-norm, for $1 \leq p \leq \infty$, and to vector-valued martingales in $\ell^2$-norm, under some strong conditions. We present as our main result a Yurinskii coupling for approximate martingales in $\ell^p$-norm, under substantially weaker conditions than those previously imposed. Our formulation further allows for the coupling variable to follow a more general Gaussian mixture distribution, and we provide a novel third-order coupling method which gives tighter approximations in certain settings. We specialize our main result to mixingales, martingales, and independent data, and derive uniform Gaussian mixture strong approximations for martingale empirical processes. Applications to nonparametric partitioning-based and local polynomial regression procedures are provided.Comment: 55 pages, 1 figur

Visual saliency and semantic incongruency influence eye movements when inspecting pictures

Models of low-level saliency predict that when we first look at a photograph our first few eye movements should be made towards visually conspicuous objects. Two experiments investigated this prediction by recording eye fixations while viewers inspected pictures of room interiors that contained objects with known saliency characteristics. Highly salient objects did attract fixations earlier than less conspicuous objects, but only in a task requiring general encoding of the whole picture. When participants were required to detect the presence of a small target, then the visual saliency of nontarget objects did not influence fixations. These results support modifications of the model that take the cognitive override of saliency into account by allowing task demands to reduce the saliency weights of task-irrelevant objects. The pictures sometimes contained incongruent objects that were taken from other rooms. These objects were used to test the hypothesis that previous reports of the early fixation of congruent objects have not been consistent because the effect depends upon the visual conspicuity of the incongruent object. There was an effect of incongruency in both experiments, with earlier fixation of objects that violated the gist of the scene, but the effect was only apparent for inconspicuous objects, which argues against the hypothesis

Tablet PCs in schools: Case study report: A report for Becta by the Open University

The publication provides an analysis of twelve case studies involving schools in England that were using Tablet PCs. The analysis is complemented by brief individual reports describing aspects of how each of these schools was using Tablet PCs

Phase behaviour of the quantum Lennard-Jones solid

The Lennard-Jones potential is perhaps one of the most widely-used models for the interaction of uncharged particles, such as noble gas solids. The phase diagram of the classical LJ solid is known to exhibit transitions between hcp and fcc phases. However, the phase behaviour of the quantum Lennard-Jones solid remains unknown. Thermodynamic integration based on path integral molecular dynamics and lattice dynamics calculations are used to study the phase stability of the hcp and fcc Lennard-Jones solids. The hcp phase is shown to be stabilized by quantum effects in PIMD while fcc is shown to be favoured by lattice dynamics, which suggests a possible re-entrant low pressure hcp phase for highly quantum systems. Implications for the phase stability of noble gas solids are discussed. For parameters equating to Helium, the expansion due to zero-point vibrations is associated with quantum melting: neither crystal structure is stable at zero pressure

Apparatus for Leak Testing Pressurized Hoses

A hose-attaching apparatus for leak-testing a pressurized hose may include a hose-attaching member. A bore may extend through the hose-attaching member. An internal annular cavity may extend coaxially around the bore. At least one of a detector probe hole and a detector probe may be connected to the internal annular cavity. At least a portion of the bore may have a diameter which is at least one of substantially equal to and less than a diameter of a hose to be leak-tested

Transforming the Productivity of People in the Built Environment: Emergence of a Digital Competency Management Ecosystem

This chapter explores how we create and support a digitally enabled, agile, competent, and ultimately, productive workforce and determines the key research questions that need to be addressed if Digital Built Britain (DBB) is to provide return on investment and succeed as the catalyst for evolving the manner in which we conceive, plan, design, construct, operate, and interact with the built environment. The proposed vision is a digital competency management ecosystem where interdependent stakeholders are incentivised to work together in coopetition to create, capture, infer, interpret, specify, integrate, accredit, apply, use, monitor, and evolve competence as a working (data) asset. This needs to be in a consistent, objective, explicit, and scalable manner, with end2end transparency and traceability for all stakeholders that overcome the challenges of competency management. Moreover, a core element must be an ecosystem organised around digital infrastructure of competency frameworks and other knowledge sources of competence, so that competency frameworks are in digital operation and dynamic context