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CSSC
2010
79views more  CSSC 2010»
14 years 10 months ago
Are Bayesian Inferences Weak for Wasserman's Example?
: An example was given in the textbook All of Statistics (Wasserman, 2004, pages 186-188) for arguing that, in the problems with a great many parameters Bayesian inferences are wea...
Longhai Li
CORR
2008
Springer
149views Education» more  CORR 2008»
14 years 10 months ago
Gaussian Belief Propagation for Solving Systems of Linear Equations: Theory and Application
The canonical problem of solving a system of linear equations arises in numerous contexts in information theory, communication theory, and related fields. In this contribution, we...
Ori Shental, Danny Bickson, Paul H. Siegel, Jack K...
CSDA
2008
128views more  CSDA 2008»
14 years 10 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
BMCBI
2006
187views more  BMCBI 2006»
14 years 10 months ago
Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false
Background: Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads ...
Harvey J. Motulsky, Ronald E. Brown
BMCBI
2006
82views more  BMCBI 2006»
14 years 10 months ago
A method for computing the overall statistical significance of a treatment effect among a group of genes
Background: In studies that use DNA arrays to assess changes in gene expression, our goal is to evaluate the statistical significance of treatments on sets of genes. Genes can be ...
Robert R. Delongchamp, Taewon Lee, Cruz Velasco