Using Decomposed Error for Reproducing Implicit Understanding of Algorithms.

Reproducibility is important for having confidence in evolutionary machine learning algorithms. Although the focus of reproducibility is usually to recreate an aggregate prediction error score using fixed random seeds, this is not sufficient. Firstly, multiple runs of an algorithm, without a fixed random seed, should ideally return statistically equivalent results.

A vector-agent approach to (spatiotemporal) movement modelling and reasoning.

Modelling a complex system of autonomous individuals moving through space and time essentially entails understanding the (heterogeneous) spatiotemporal context, interactions with other individuals, their internal states and making any underlying causal interrelationships explicit, a task for which agents (including vector-agents) are specifically well-suited. Building on a conceptual model of agent space-time and reasoning behaviour, a design guideline for an implemented vector-agent model is presented. The movement of football players was chosen as it is appropriately constrained in space, time and individual actions.

Graph-structured populations and the Hill-Robertson effect.

The Hill-Robertson effect describes how, in a finite panmictic diploid population, selection at one diallelic locus reduces the fixation probability of a selectively favoured allele at a second, linked diallelic locus. Here we investigate the influence of population structure on the Hill-Robertson effect in a population of size . We model population structure as a network by assuming that individuals occupy nodes on a graph connected by edges that link members who can reproduce with each other.

Managing distance and covariate information with point-based clustering.

Background: Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures.

Matrix matters: differences of grand skink metapopulation parameters in native tussock grasslands and exotic pasture grasslands.

Modelling metapopulation dynamics is a potentially very powerful tool for conservation biologists. In recent years, scientists have broadened the range of variables incorporated into metapopulation modelling from using almost exclusively habitat patch size and isolation, to the inclusion of attributes of the matrix and habitat patch quality. We investigated the influence of habitat patch and matrix characteristics on the metapopulation parameters of a highly endangered lizard species, the New Zealand endemic grand skink (Oligosoma grande) taking into account incomplete detectability.

Neighbourhood deprivation and access to alcohol outlets: a national study.

People living in poor areas suffer higher mortality than those in wealthy areas. Environmental factors partly explain this association, including exposure to pollutants and accessibility of healthcare. We sought to determine whether proximity to alcohol outlets varied by area deprivation in New Zealand.

Genetic drift on networks: ploidy and the time to fixation.

Genetic drift in finite populations ultimately leads to the loss of genetic variation. This paper examines the rate of neutral gene loss for a range of population structures defined by a graph. We show that, where individuals reside at fixed points on an undirected graph with equal degree nodes, the mean time to loss differs from the panmictic value by a positive additive term that depends on the number of individuals (not genes) in the population.