Fast Kernel Smoothing in R with Applications to Projection Pursuit

This paper introduces the R package FKSUM, which offers fast and exact evaluation of univariate kernel smoothers. The main kernel computations are implemented in C++, and are wrapped in simple, intuitive and versatile R functions. The fast kernel computations are based on recursive expressions involving the order statistics, which allows for exact evaluation of kernel smoothers at all sample points in log-linear time. In addition to general purpose kernel smoothing functions, the package offers purpose built and readyto-use implementations of popular kernel-type estimators. On top of these basic smoothing problems, this paper focuses on projection pursuit problems in which the projection index is based on kernel-type estimators of functionals of the projected density

Minimum Density Hyperplanes

Associating distinct groups of objects (clusters) with contiguous regions of high probability density (high-density clusters), is central to many statistical and machine learning approaches to the classification of unlabelled data. We propose a novel hyperplane classifier for clustering and semi-supervised classification which is motivated by this objective. The proposed minimum density hyperplane minimises the integral of the empirical probability density function along it, thereby avoiding intersection with high density clusters. We show that the minimum density and the maximum margin hyperplanes are asymptotically equivalent, thus linking this approach to maximum margin clustering and semi-supervised support vector classifiers. We propose a projection pursuit formulation of the associated optimisation problem which allows us to find minimum density hyperplanes efficiently in practice, and evaluate its performance on a range of benchmark datasets. The proposed approach is found to be very competitive with state of the art methods for clustering and semi-supervised classification

Exploring South Africa’s southern frontier: A 20-year vision for polar research through the South African National Antarctic Programme

Antarctica, the sub-Antarctic islands and surrounding Southern Ocean are regarded as one of the planet’s last remaining wildernesses, ‘insulated from threat by [their] remoteness and protection under the Antarctic Treaty System’1 . Antarctica encompasses some of the coldest, windiest and driest habitats on earth. Within the Southern Ocean, sub-Antarctic islands are found between the Sub-Antarctic Front to the north and the Polar Front to the south. Lying in a transition zone between warmer subtropical and cooler Antarctic waters, these islands are important sentinels from which to study climate change.2 A growing body of evidence3,4 now suggests that climatically driven changes in the latitudinal boundaries of these two fronts define the islands’ short- and long-term atmospheric and oceanic circulation patterns. Consequently, sub-Antarctic islands and their associated terrestrial and marine ecosystems offer ideal natural laboratories for studying ecosystem response to change.5 For example, a recent study6 indicates that the shift in the geographical position of the oceanic fronts has disrupted inshore marine ecosystems, with a possible impact on top predators. Importantly, biotic responses are variable as indicated by different population trends of these top predators.7,8 When studied collectively, these variations in species’ demographic patterns point to complex spatial and temporal changes within the broader sub-Antarctic ecosystem, and invite further examination of the interplay between extrinsic and intrinsic drivers

Increasing access to institutional deliveries using demand and supply side incentives: early results from a quasi-experimental study

<p>Abstract</p> <p>Background</p> <p>Geographical inaccessibility, lack of transport, and financial burdens are some of the demand side constraints to maternal health services in Uganda, while supply side problems include poor quality services related to unmotivated health workers and inadequate supplies. Most public health interventions in Uganda have addressed only selected supply side issues, and universities have focused their efforts on providing maternal services at tertiary hospitals. To demonstrate how reforms at Makerere University College of Health Sciences (MakCHS) can lead to making systemic changes that can improve maternal health services, a demand and supply side strategy was developed by working with local communities and national stakeholders.</p> <p>Methods</p> <p>This quasi-experimental trial is conducted in two districts in Eastern Uganda. The supply side component includes health worker refresher training and additions of minimal drugs and supplies, whereas the demand side component involves vouchers given to pregnant women for motorcycle transport and the payment to service providers for antenatal, delivery, and postnatal care. The trial is ongoing, but early analysis from routine health information systems on the number of services used is presented.</p> <p>Results</p> <p>Motorcyclists in the community organized themselves to accept vouchers in exchange for transport for antenatal care, deliveries and postnatal care, and have become actively involved in ensuring that women obtain care. Increases in antenatal, delivery, and postnatal care were demonstrated, with the number of safe deliveries in the intervention area immediately jumping from <200 deliveries/month to over 500 deliveries/month in the intervention arm. Voucher revenues have been used to obtain needed supplies to improve quality and to pay health workers, ensuring their availability at a time when workloads are increasing.</p> <p>Conclusions</p> <p>Transport and service vouchers appear to be a viable strategy for rapidly increasing maternal care. MakCHS can design strategies together with stakeholders using a learning-by-doing approach to take advantage of community resources.</p