This article considers an analogous problem in which the observed random variables are the steps of a symmetric random walk. Assuming continuously distributed step sizes, it describes the optimal stopping rules for the cases n = 2 and n = 3 in two versions of the problem: a "full information" version in which the actual steps of the random walk are disclosed to the decision maker; and a "partial information" version in which only the relative ranks of the positions taken by the random walk are observed. When n = 3, the optimal rule and expected rank depend on the distribution of the step sizes. The authors give sharp bounds for the optimal expected rank in the partial information version, and fairly sharp bounds in the full information version.

This article summarizes the contributions from the Genome-wide Association Study group (GWAS group) of the GAW20. The GWAS group contributions focused on topics such as association tests, phenotype imputation, and application of empirical kinships. This summary article reports on promising statistical approaches and findings of the members of the GWAS group applied on real and simulated data which encompass the current topics of epigenetic and pharmacogenomics.

This article reports on promising statistical approaches and findings of the members of the Genome-wide Association Study group applied on real and simulated data which encompass the current topics of epigenetic and pharmacogenomics.

This article discusses the development of two statistical methods to test the gene environment interaction effect of rare variants.

Article presents an overview of the data sets and the contributions analyzing data related to human lipid-related phenotypes, DNA methylation, and single-nucleotide markers in a study involving a pharmaceutical intervention.