A Bayesian hierarchical model for allele frequencies

A Bayesian hierarchical model for allele frequencies.

Genetic epidemiological methodologies, such as linkage analysis, often require accurate estimates of allele frequencies. When studies involve multiple sub-populations with different evolutionary histories, accurate estimates can be difficult to obtain because the number of subjects per sub-population tends to be limited. Given allele counts for a collection of loci and sub-populations, we propo...

Allele Frequencies and Genotype Frequencies

A Bayesian Hierarchical Model for Photometric Redshifts

The Sloan Digital Sky Survey (SDSS) is an extremely large astronomical survey conducted with the intention of mapping more than a quarter of the sky (http://www.sdss.org/). Among the data it is generating are spectroscopic and photometric measurements, both allowing estimation of the redshift of galaxies. The former is precise but expensive to gather, the latter is far cheaper but corresponding...

A Hierarchical Bayesian Model for Topic Segmentation

Many streams of real-world data, such as conversations or body movements, consist of relatively coherent segments, each characterized by particular topics or controllers. Making sense of these data requires simultaneously segmenting the sequences and inferring the structure of the segments. We present a hierarchical Bayesian model that can be used to break a sequence of utterances or movements ...

A Hierarchical Bayesian Model for Crowd Emotions

Estimation of emotions is an essential aspect in developing intelligent systems intended for crowded environments. However, emotion estimation in crowds remains a challenging problem due to the complexity in which human emotions are manifested and the capability of a system to perceive them in such conditions. This paper proposes a hierarchical Bayesian model to learn in unsupervised manner the...