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Estimation of Selection Parameters using Multi‐generation Cytonuclear Data
Author(s) -
Datta Susmita
Publication year - 2001
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/1521-4036(200105)43:2<219::aid-bimj219>3.0.co;2-5
Subject(s) - mathematics , selection (genetic algorithm) , estimator , statistics , simple random sample , best linear unbiased prediction , population , covariance , locus (genetics) , computer science , biology , genetics , artificial intelligence , demography , sociology , gene
We have developed an approximate maximum likelihood framework for the problem of estimating the selection coefficients in a simple fertility selection model via random union of zygotes. We consider a sampling scheme where a random sample from each (discrete) generation of a population observed over several generations is collected and genotyped based on one nuclear locus and a cytonuclear locus, simultaneously. Simulation results show excellent small sample performance of the resulting approximate MLE. Asymptotic variance‐covariance matrix of our estimator is also obtained. We further show that these estimates can be used to obtain simple test statistics for testing various types of selection hypotheses including a test of neutrality.