Coalescence computations for large samples drawn from populations of time-varying sizes

Coalescence computations for large samples drawn from populations of time-varying sizes

We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applicatio...

A Modified X̄Control Chart for Samples Drawn from Finite Populations

Time-Varying Systems and Computations Lecture 3

Asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size.

The distributions of coalescence times and ancestral lineage numbers play an essential role in coalescent modeling and ancestral inference. Both exact distributions of coalescence times and ancestral lineage numbers are expressed as the sum of alternating series, and the terms in the series become numerically intractable for large samples. More computationally attractive are their asymptotic di...

Online Learning with Samples Drawn from Non-identical Distributions

Learning algorithms are based on samples which are often drawn independently from an identical distribution (i.i.d.). In this paper we consider a different setting with samples drawn according to a non-identical sequence of probability distributions. Each time a sample is drawn from a different distribution. In this setting we investigate a fully online learning algorithm associated with a gene...