Statistics Research: Recent submissions

Now showing items 6-10 of 10

    • Distance software: design and analysis of distance sampling surveys for estimating population size 

      Thomas, Len; Buckland, Stephen Terrence; Rexstad, Eric; Laake, J L; Strindberg, S; Hedley, S L; Bishop, J R B; Marques, Tiago A. (2010) - Journal article
      1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling ...

    • The importance of analysis method for breeding bird survey population trend estimates 

      Thomas, Len; Martin, Kathy (1996) - Journal article
      Population trends from the Breeding Bird Survey are widely used to focus conservation efforts on species thought to be in decline and to test preliminary hypotheses regarding the causes of these declines. A number of ...

    • Retrospective power analysis 

      Thomas, Len (1997) - Journal article
      Many papers have appeared in the recent biological literature encouraging us to incorporate statistical power analysis into our hypothesis testing protocol (Peterman 1990; Fairweather 1991; Muller & Benignus 1992; Taylor ...

    • A unified framework for modelling wildlife population dynamics 

      Thomas, Len; Buckland, Stephen T.; Newman, KB; Harwood, John (2005) - Journal article
      This paper proposes a unified framework for defining and fitting stochastic, discrete-time, discrete-stage population dynamics models. The biological system is described by a state–space model, where the true but unknown ...

    • WinBUGS for population ecologists: Bayesian modeling using Markov Chain Monte Carlo methods. 

      Giminez, O; Bonner, S J; King, Ruth; Parker, R A; Brooks, S P; Jamieson, L E; Grosbois, V; Morgan, B J T; Thomas, Len (Springer Series: Environmental and Ecological Statistics, 2008) - Book item
      The computer package WinBUGS is introduced. We first give a brief introduction to Bayesian theory and its implementation using Markov chain Monte Carlo (MCMC) algorithms. We then present three case studies showing how ...