A Bayesian model averaging approach for observational gene expression studies
نویسندگان
چکیده
منابع مشابه
Predicting waste generation using Bayesian model averaging
A prognosis model has been developed for solid waste generation from households in Hoi An City, a famous tourist city in Viet Nam. Waste sampling, followed by a questionnaire survey, was carried out to gather data. The Bayesian model average method was used to identify factors significantly associated with waste generation. Multivariate linear regression analysis was then applied to evaluate th...
متن کاملPrognostic Factors for Urachal Cancer: A Bayesian Model-Averaging Approach
PURPOSE This study was conducted to evaluate prognostic factors and cancer-specific survival (CSS) in a cohort of 41 patients with urachal carcinoma by use of a Bayesian model-averaging approach. MATERIALS AND METHODS Our cohort included 41 patients with urachal carcinoma who underwent extended partial cystectomy, total cystectomy, transurethral resection, chemotherapy, or radiotherapy at a s...
متن کاملFinding Good Predictors for Inflation: A Bayesian Model Averaging Approach
We consider a Bayesian Model Averaging approach for the purpose of forecasting Swedish consumer price index inflation using a large set of potential indicators, comprising some 80 quarterly time series covering a wide spectrum of Swedish economic activity. The paper demonstrates how to efficiently and systematically evaluate (almost) all possible models that these indicators in combination can ...
متن کاملClustering Gene Expression Profiles Using Mixture Model Ensemble Averaging Approach
Clustering has been an important tool for extracting underlying gene expression patterns from massive microarray data. However, most of the existing clustering methods cannot automatically separate noise genes, including scattered, singleton and mini-cluster genes, from other genes. Inclusion of noise genes into regular clustering processes can impede identification of gene expression patterns....
متن کاملBayesian Model Averaging: A Tutorial
Standard statistical practice ignores model uncertainty. Data analysts typically select a model from some class of models and then proceed as if the selected model had generated the data. This approach ignores the uncertainty in model selection, leading to over-confident inferences and decisions that are more risky than one thinks they are. Bayesian model averaging (BMA) provides a coherent mec...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Applied Statistics
سال: 2012
ISSN: 1932-6157
DOI: 10.1214/11-aoas526