Package: csmGmm
Type: Package
Title: Conditionally Symmetric Multidimensional Gaussian Mixture Model
Version: 0.5.0
Authors@R: c(
	person("Ryan", "Sun", email = "ryansun.work@gmail.com", role = c("aut", "cre")),
	person("Emily", "Kim", role="aut"))
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 (Journal of the American Statistical Association 2025,
        <doi:10.1080/01621459.2024.2422124>).
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.3
Imports: dplyr, mvtnorm, curl, data.table, ggplot2, rlang, magrittr,
        stats, utils
Suggests: knitr, rmarkdown, R.utils
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-16 09:16:38 UTC; root
Author: Ryan Sun [aut, cre], Emily Kim [aut]
Maintainer: Ryan Sun <ryansun.work@gmail.com>
Depends: R (>= 4.1.0)
Config/pak/sysreqs: libssl-dev
Repository: https://ryansunwork.r-universe.dev
Date/Publication: 2026-06-16 17:26:37 UTC
RemoteUrl: https://github.com/cran/csmGmm
RemoteRef: HEAD
RemoteSha: fd3fd9167e83020f905639cca271f2bdd75095a1