|
In population genetics, Ewens' sampling formula, describes the probabilities associated with counts of how many different alleles are observed a given number of times in the sample. ==Definition== Ewens' sampling formula, introduced by Warren Ewens, states that under certain conditions (specified below), if a random sample of ''n'' gametes is taken from a population and classified according to the gene at a particular locus then the probability that there are ''a''1 alleles represented once in the sample, and ''a''2 alleles represented twice, and so on, is : for some positive number ''θ'' representing the population mutation rate, whenever ''a''1, ..., ''a''''n'' is a sequence of nonnegative integers such that : The phrase "under certain conditions" used above is made precise by the following assumptions: * The sample size ''n'' is small by comparison to the size of the whole population; and * The population is in statistical equilibrium under mutation and genetic drift and the role of selection at the locus in question is negligible; and * Every mutant allele is novel. (See also infinite-alleles model.) This is a probability distribution on the set of all partitions of the integer ''n''. Among probabilists and statisticians it is often called the multivariate Ewens distribution. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Ewens's sampling formula」の詳細全文を読む スポンサード リンク
|