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csmGmm  

Conditionally Symmetric Multidimensional Gaussian Mixture Model
View on CRAN: Click here


Download and install csmGmm package within the R console
Install from CRAN:
install.packages("csmGmm")

Install from Github:
library("remotes")
install_github("cran/csmGmm")

Install by package version:
library("remotes")
install_version("csmGmm", "0.3.0")



Attach the package and use:
library("csmGmm")
Maintained by
Ryan Sun
[Scholar Profile | Author Map]
First Published: 2024-12-03
Latest Update: 2024-12-03
Description:
Implements the conditionally symmetric multidimensional Gaussian mixture model (csmGmm) for large-scale testing of composite null hypotheses in genetic association applications such as mediation analysis, pleiotropy analysis, and replication analysis. In such analyses, we typically have J sets of K test statistics where K is a small number (e.g. 2 or 3) and J is large (e.g. 1 million). For each one of the J sets, we want to know if we can reject all K individual nulls. Please see the vignette for a quickstart guide. The paper describing these methods is "Testing a Large Number of Composite Null Hypotheses Using Conditionally Symmetric Multidimensional Gaussian Mixtures in Genome-Wide Studies" by Sun R, McCaw Z, & Lin X (2024, <doi:10.1080/01621459.2024.2422124>). The paper is accepted and published online (but not yet in print) in the Journal of the American Statistical Association as of Dec 1 2024.
How to cite:
Ryan Sun (2024). csmGmm: Conditionally Symmetric Multidimensional Gaussian Mixture Model. R package version 0.3.0, https://cran.r-project.org/web/packages/csmGmm. Accessed 21 Feb. 2025.
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