Computational methods for the coalescent. (English) Zbl 0893.92021
Donnelly, Peter (ed.) et al., Progress in population genetics and human evolution. Proceedings of the workshop on Mathematical population genetics, held at the IMA, Minnesota, MN, USA, January 24–28, 1994. New York, NY: Springer. IMA Vol. Math. Appl. 87, 165-182 (1997).
Summary: This paper describes recent work on computational methods for the coalescent. We show how integro-recurrence relations for sampling distributions and related quantities may be solved by a simple Markov chain Monte Carlo method. We describe the method in the context of the coalescent process for a population that is evolving according to a deterministic population size function. The usual constant population size models appear as a special case of this approach. One of the appealing features of the approach is its generic nature: many apparently different problems may be attacked with this one approach. A wide variety of examples are discussed, among them maximum likelihood estimation of parameters.
For the entire collection see [Zbl 0861.00030].
For the entire collection see [Zbl 0861.00030].
MSC:
| 92D15 | Problems related to evolution |
| 60G35 | Signal detection and filtering (aspects of stochastic processes) |
| 92-08 | Computational methods for problems pertaining to biology |
| 60J20 | Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) |
