Published online by Cambridge University Press: 01 July 2016
For N = 1, 2, …, let {(XN (k), YN (k)), k = 0, 1, …} be a time-homogeneous Markov chain in . Suppose that, asymptotically as N → ∞, the ‘infinitesimal' covariances and means of XN([·/ε N]) are aij(x, y) and bi(x, y), and those of YN ([·/δ N]) are 0 and cl(x, y). Assume
and limN→∞ε N/δ N = 0. Then, under a global asymptotic stability condition on dy/dt = c(x, y) or a related difference equation (and under some technical conditions), it is shown that (i) XN([·/ε N]) converges weakly to a diffusion process with coefficients aij(x, 0) and bi(x, 0) and (ii) YN([t/ε N]) → 0 in probability for every t > 0. The assumption in Ethier and Nagylaki (1980) that the processes are uniformly bounded is removed here.
The results are used to establish diffusion approximations of multiallelic one-locus stochastic models for mutation, selection, and random genetic drift in a finite, panmictic, diploid population. The emphasis is on rare, severely deleterious alleles. Models with multinomial sampling of genotypes in the monoecious, dioecious autosomal, and X-linked cases are analyzed, and an explicit formula for the stationary distribution of allelic frequencies is obtained.
Supported in part by NSF grant DMS-8403648.
Supported in part by NSF grant BSR-8512844.
In general, Ez[f(ZN(1))] denotes the integral of f with respect to the one-step transition function of ZN(·) starting at z; a similar convention applies to probabilities, variances, and covariances.
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