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Summary. Functional magnetic resonance imaging (MRI) is an advanced technology for studying brain functions. Owing to the complexity and high cost of functional MRI experiments, high quality multiobjective functional MRI designs are in great demand; they help to render precise statistical inference and are keys to the success of functional MRI experiments. Here, we propose an efficient approach for...
Summary. In ecology, a common form of statistical analysis relates a biological variable to variables that delineate the physical environment, typically by fitting a regression model or one of its extensions. Unfortunately, the biological data and the physical data are frequently obtained from separate sources of data. In such cases there is no guarantee that the biological and physical data are...
Summary. The paper adapts sparse factor models for exploring covariation in multivariate binary data, with an application to measuring latent factors in US Congressional roll‐call voting patterns. This straightforward modification provides two advantages over traditional factor analysis of binary data. First, a sparsity prior can be used to assess the evidence that a given factor loading may be exactly...
Summary. Determination of a clinical trial's size is an important task in the planning of any trial because of the direct implications of the sample size on feasibility, costs and timelines. However, sample size calculations are often subject to substantial uncertainty due to limited prior information on the size of nuisance parameters such as variances or event rates. Continuous monitoring of the...
Summary. Very‐short‐term probabilistic forecasts, which are essential for an optimal management of wind generation, ought to account for the non‐linear and double‐bounded nature of that stochastic process. They take here the form of discrete–continuous mixtures of generalized logit–normal distributions and probability masses at the bounds. Both auto‐regressive and conditional parametric auto‐regressive...
Summary. Climate change may lead to changes in several aspects of the distribution of climate variables, including changes in the mean, increased variability and severity of extreme events. We propose the use of spatiotemporal quantile regression as a flexible and interpretable method for simultaneously detecting changes in several features of the distribution of climate variables. The spatiotemporal...
Summary. The paper develops a significance test for evaluating the equality of the mean functions in two samples of spatially indexed functional data. The problem is motivated by an important question in space physics research which is related to the hypothesis of ionospheric global cooling (as opposed to the conjectured global warming of near surface atmosphere). The critical electron frequency...
Summary. The simplest states of finite quantum systems are the pure states. The paper is motivated by the need to test statistically whether or not a given physical state is pure. Because the pure states lie in the boundary of the set of all states, the usual regularity conditions that justify the standard large sample approximations to the null distributions of the deviance and the score statistic...
Summary. The complex interrelated nature of multivariate systems can result in relationships and covariance structures that change over time. Smooth principal components analysis is proposed as a means of investigating whether and how the covariance structure of multiple response variables changes over time, after removing a smooth function for the mean, and this is motivated and illustrated by using...
Summary. When using computer models to provide policy support it is normal to encounter ensembles that test only a handful of feasible or idealized decision scenarios. We present a new methodology for performing multilevel emulation of a complex model as a function of any decision within a predefined class that makes specific use of a scenario ensemble of opportunity on a fast or early version of...
Summary. Caloric restriction (CR) has been shown to delay the onset of cancer and other diseases that are associated with aging. Currently there are very few studies examining the whole‐animal physiological response to late onset CR. We study the ways by which mice physiologically compensate for reduced availability of food given exposure to late onset CR and compare these with mice fed ad libitum...
Summary. We compare two techniques that are widely used in the analysis of life course trajectories: latent class analysis and sequence analysis. In particular, we focus on the use of these techniques as devices to obtain classes of individual life course trajectories. We first compare the consistency of the classification that is obtained via the two techniques by using a data set on the life course...
Summary. We analyse the education–fertility relationship by using data on women from Botswana. A realistic quantification of such a relationship can be problematic for various reasons. First, factors such as motivation and ability are associated with fertility and education but cannot be observed and as a consequence cannot be included in the model. Here, the use of classical estimation methods will...
Summary. In the course of national sports tournaments, usually lasting several months, it is expected that the abilities of teams taking part in the tournament will change over time. A dynamic extension of the Bradley–Terry model for paired comparison data is introduced to model the outcomes of sporting contests, allowing for time varying abilities. It is assumed that teams’ home and away abilities...
Summary. This work is concerned with the vulnerability of spaceborne microelectronics to single‐event upset, which is a change of state caused by high‐energy charged particles in the solar wind or the cosmic ray environment striking a sensitive node. To measure the susceptibility of a semiconductor device to single‐event upsets, testing is conducted by exposing it to high‐energy heavy ions or protons...
Summary. A common conjecture in the study of publication bias is that studies reporting a significant result are more likely to be selected for review than studies whose results are inconclusive. We envisage a population of studies following the standard random‐effects model of meta‐analysis, and a selection probability given by a function of the study's ‘t‐statistic’. In practice it is difficult...
Summary. Climate change will affect the insurance industry. We develop a Bayesian hierarchical statistical approach to explain and predict insurance losses due to weather events at a local geographic scale. The number of weather‐related insurance claims is modelled by combining generalized linear models with spatially smoothed variable selection. Using Gibbs sampling and reversible jump Markov chain...
Summary. Data are often collected from wild animals that have been marked at unknown age. As a result, standard probability models, fitted by maximum likelihood, cannot incorporate age dependence in probabilities of annual survival. We propose and fit new mixture models to ring–recovery data on birds ringed of unknown age, in which it is possible to incorporate age dependence in survival. It is shown...
Summary. Typical oncology practice often includes not only an initial front‐line treatment but also subsequent treatments given if the initial treatment fails. The physician chooses a treatment at each stage based on the patient's baseline covariates and history of previous treatments and outcomes. Such sequentially adaptive medical decision‐making processes are known as dynamic treatment regimes,...
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