32 citations · 74 across the 4 of their papers we have counts for
5 papers
A fast algorithm for maximum likelihood estimation of mixture proportions using sequential quadratic programming
Youngseok Kim, Peter Carbonetto, Matthew Stephens +1
Maximum likelihood estimation of mixture proportions has a long history, and continues to play an important role in modern statistics, including in development of nonparametric emp…
varbvs: Fast Variable Selection for Large-scale Regression
Peter Carbonetto, Xiang Zhou, Matthew Stephens
We introduce varbvs, a suite of functions written in R and MATLAB for regression analysis of large-scale data sets using Bayesian variable selection methods. We have developed nume…
Polygenic Modeling with Bayesian Sparse Linear Mixed Models
Xiang Zhou, Peter Carbonetto, Matthew Stephens
Both linear mixed models (LMMs) and sparse regression models are widely used in genetics applications, including, recently, polygenic modeling in genome-wide association studies. T…
Integrated analysis of variants and pathways in genome-wide association studies using polygenic models of disease
Peter Carbonetto, Matthew Stephens
Many common diseases are highly polygenic, modulated by a large number genetic factors with small effects on susceptibility to disease. These small effects are difficult to map rel…
Nonparametric Bayesian Logic
Peter Carbonetto, Jacek Kisynski, Nando de Freitas +1
The Bayesian Logic (BLOG) language was recently developed for defining first-order probability models over worlds with unknown numbers of objects. It handles important problems in…