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Now showing items 1-10 of 19

#### Distributions of gene tree branch lengths under coalescence

(University of Canterbury. Mathematics and Statistics, 2008)

In Bayesian phylogenetic inference, commonly used prior distributions for branch lengths are the uniform, exponential, and gamma distributions. We derive the exact distributions of branch lengths of gene trees under a fixed ...

#### Calculation of fix-rate bias for automated telemetry systems

(University of Canterbury. Mathematics and Statistics, 2009)

#### A New Adaptive Sequential Design for Sampling Rare and Clustered Populations

(University of Canterbury. Mathematics and StatisticsUniversity of Canterbury. Management, 2008)

Designing an efficient large-area survey is a challenge for ecologists. Adaptive sampling designs can be efficient because it ensures survey effort is targeted to subareas of high interest. In two-stage sampling, higher ...

#### Bounding the Number of Hybridisation Events for a Consistent Evolutionary History

(University of Canterbury. Mathematics and Statistics., 2005)

#### Counting consistent phylogenetic trees is #P-complete

(University of Canterbury. Mathematics and Statistics., 2004)

Reconstructing phylogenetic trees is a fundamental task in evolutionary biology. Various algorithms exist for this purpose, many of
which come under the heading of `supertree methods'. These methods
amalgamate a collection ...

#### A unified multi-resolution coalescent: Markov lumpings of the Kingman-Tajima n-coalescent

(Department of Mathematics & StatisticsUniversity of Canterbury. Mathematics and Statistics, 2009)

In this paper, we formulate six different resolutions of a continuous-time approximation of the Wright-Fisher sample genealogical process. We derive Markov chains for the six different approximations in the spirit of J.F.C. ...

#### Coalescent experiments I: Unlabeled n-coalescent and the site frequency spectrum

(Department of Mathematics & StatisticsUniversity of Canterbury. Mathematics and Statistics, 2009)

We derive the transition structure of a Markovian lumping of Kingman’s n-coalescent [1, 2]. Lumping a Markov chain is meant in the sense of [3, def. 6.3.1]. The lumped Markov process, referred as the
unlabeled n-coalescent, ...

#### Coalescent experiments II: Markov bases of classical population genetic statistics

(Department of Mathematics & StatisticsUniversity of Canterbury. Mathematics and Statistics, 2009)

Evaluating the likelihood function of parameters in complex population genetic models from extant deoxyribonucleic acid (DNA) sequences is computationally prohibitive. In such cases, one may approximately infer the parameters ...

#### Rescuing concatenation with maximum likelihood using supermatrix rooted triples

(University of Canterbury. Mathematics and Statistics, 2009)

Concatenated alignments are often used to infer species-level reslationships. Previous studies have shown that analysis of concatenated alignments using maximum likelihood
(ML) can produce misleading results. We develop ...

#### Graphical Modeling of Ecological Time Series Data

(University of Canterbury. Mathematics and Statistics., 2007)

Graphical models offer a powerful tool for
studying ecosystem function. Changes in
relationships among extrinsic and intrinsic
biological and environmental variables can be
explored. We discuss the application of ...