University of New Brunswick

About: University of New Brunswick is a education organization based out in Fredericton, New Brunswick, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 10498 authors who have published 20654 publications receiving 474448 citations.

Residual analysis for spatial point processes (with discussion)

Abstract: Summary. We define residuals for point process models fitted to spatial point pattern data, and we propose diagnostic plots based on them. The residuals apply to any point process model that has a conditional intensity; the model may exhibit spatial heterogeneity, interpoint interaction and dependence on spatial covariates. Some existing ad hoc methods for model checking (quadrat counts, scan statistic, kernel smoothed intensity and Berman's diagnostic) are recovered as special cases. Diagnostic tools are developed systematically, by using an analogy between our spatial residuals and the usual residuals for (non-spatial) generalized linear models. The conditional intensity λ plays the role of the mean response. This makes it possible to adapt existing knowledge about model validation for generalized linear models to the spatial point process context, giving recommendations for diagnostic plots. A plot of smoothed residuals against spatial location, or against a spatial covariate, is effective in diagnosing spatial trend or co-variate effects. Q–Q-plots of the residuals are effective in diagnosing interpoint interaction.

Further Notes on the Basic Reproduction Number

Abstract: The basic reproduction number, R0 is a measure of the potential for disease spread in a population. Mathematically, R0 is a threshold for stability of a disease-free equilibrium and is related to the peak and final size of an epidemic. The purpose of these notes is to give a precise definition and algorithm for obtaining R0 for a general compartmental ordinary differential equation model of disease transmission. Several examples of calculating R0 are included, and the epidemiological interpretation of this threshold parameter is connected to the local and global stability of a disease-free equilibrium.

Challenges in Understanding the Influence of Maximal Power Training on Improving Athletic Performance

Abstract: The ability to optimise muscular power output is considered fundamental to successful performance of many athletic and sporting activities. Consequently, a great deal of research has investigated methods to improve power output and its transference to athletic performance. One issue that makes comparisons between studies difficult is the different modes of dynamometry (isometric, isokinetic and isoinertial) used to measure strength and power. However, it is recognised that isokinetic and isometric assessment bear little resemblance to the accelerative/decelerative motion implicit in limb movement during resistance training and sporting performance. Furthermore, most people who train to increase power would have limited or no access to isometric and/or isokinetic dynamometry. It is for these reasons and for the sake of brevity that the findings of isoinertial (constant gravitational load) research will provide the focus of much of the discussion in this review.