Ken Newman

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Principal Researcher in Statistical Methodology

Biomathematics and Statistics Scotland
JCMB, The King's Buildings,
Peter Guthrie Tait Road,
EDINBURGH, EH9 3FD, Scotland, UK

Tel: +44 (0)131 650 5056

Ken Newman

Research Interests and Areas of Application

I coordinate BioSS research in the Statistical Methodology Research Theme. In this Theme, we develop and advance statistical methods for data collection and analysis to help answer challenging and wide-ranging scientific questions related to agriculture and the rural economy, the environment, food and health. Some methods and areas of current focus include:

My main area of personal research interest is state-space models in particular, and hierarchical models in general. This includes developing procedures for combining multiple data sets that provide separate information about different processes, such as (in a population dynamics context) survival, reproduction, and movement, the process of combination leading to what is sometimes referred to as an integrated analysis. Given such models, I am also interested in developing decision-support tools for domain-specific researchers and resource managers to use such models to do things like predict the long-term effects of management actions on some resource.

Statistical analyses are limited by the quality of data available, hence I have a long-standing interest in statistical sampling theory and methods. This includes methods for sampling spatially-referenced populations and the design and implementation of long-term monitoring programs for determining status and trends in ecological systems.

In general I'm very interested in collaborative interdisciplinary science projects where sound statistical practices are central and where statistical methodology needs to be tailored or expanded upon to better achieve project aims. My strongest application area is population modelling, including heavily managed populations of economic importance. I am also interested in a much broader sphere of activities including the development of hierarchical models for other dynamic natural systems such as agricultural crop growth and yield, plant growth, and hydrology.

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