Filtering the Wright-Fisher diffusion

Mireille Chaleyat-Maurel; Valentine Genon-Catalot

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arXiv · 0707.0537

Filtering the Wright-Fisher diffusion

Mireille Chaleyat-Maurel·Valentine Genon-Catalot

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Abstract

We consider a Wright-Fisher diffusion (x(t)) whose current state cannot be observed directly. Instead, at times t1 < t2 < . . ., the observations y(ti) are such that, given the process (x(t)), the random variables (y(ti)) are independent and the conditional distribution of y(ti) only depends on x(ti). When this conditional distribution has a specific form, we prove that the model ((x(ti), y(ti)), i 1) is a computable filter in the sense that all distributions involved in filtering, prediction and smoothing are exactly computable. These distributions are expressed as finite mixtures of parametric distributions. Thus, the number of statistics to compute at each iteration is finite, but this number may vary along iterations.

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BibTeX RIS

Mireille Chaleyat-Maurel, Valentine Genon-Catalot. 2007-07-04. Filtering the Wright-Fisher diffusion. https://arxiv.org/abs/0707.0537

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