Maximum likelihood estimation of population parameters
Journal Article
·
· Genetics; (United States)
OSTI ID:5428871
- Univ. of Texas, Houston, TX (United States)
One of the most important parameters in population genetics is [theta] = 4N[sub e][mu] where N[sub e] is the effective population size and [mu] is the rate of mutation per gene per generation. The authors study two related problems, using the maximum likelihood method and the theory of coalescence. One problem is the potential improvement of accuracy in estimating the parameter [theta] over existing methods and the other is the estimation of parameter [lambda] which is the ratio of two [theta]'s. The minimum variances serve as the lower bounds of the variances of all possible estimates of [theta] in practice. The authors then show that Watterson's estimate of [theta] based on the number of segregating sites is asymptotically an optimal estimate of [theta]. However, for a finite sample of sequences, substantial improvement over Watterson's estimate is possible when [theta] is large. The maximum likelihood estimate of [lambda] = [theta][sub 1]/[theta][sub 2] is obtained and the properties of the estimate are discussed. 9 refs., 3 figs., 3 tabs.
- OSTI ID:
- 5428871
- Journal Information:
- Genetics; (United States), Journal Name: Genetics; (United States) Vol. 134:4; ISSN GENTAE; ISSN 0016-6731
- Country of Publication:
- United States
- Language:
- English
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