Package: mixedCCA 1.6.2
Irina Gaynanova
mixedCCA: Sparse Canonical Correlation Analysis for High-Dimensional Mixed Data
Semi-parametric approach for sparse canonical correlation analysis which can handle mixed data types: continuous, binary and truncated continuous. Bridge functions are provided to connect Kendall's tau to latent correlation under the Gaussian copula model. The methods are described in Yoon, Carroll and Gaynanova (2020) <doi:10.1093/biomet/asaa007> and Yoon, Mueller and Gaynanova (2021) <doi:10.1080/10618600.2021.1882468>.
Authors:
mixedCCA_1.6.2.tar.gz
mixedCCA_1.6.2.tar.gz(r-4.5-noble)mixedCCA_1.6.2.tar.gz(r-4.4-noble)
mixedCCA_1.6.2.tgz(r-4.4-emscripten)mixedCCA_1.6.2.tgz(r-4.3-emscripten)
mixedCCA.pdf |mixedCCA.html✨
mixedCCA/json (API)
| # Install 'mixedCCA' in R: |
| install.packages('mixedCCA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:853a853ee9. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 06 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 06 2024 |
Exports:autocorblockcorestimateRestimateR_mixedfind_w12bicGenerateDataKendall_matrixKendallTaulambdaseq_generatemixedCCAmyrccstandardCCA
Dependencies:abindaskpassassertthatbase64encbslibcacachemcallrcliclustercodetoolscolorspacecpp11crosstalkcubaturecurldata.tabledendextenddigestdoFuturedoRNGdplyreggevaluatefansifarverfastmapfBasicsfMultivarfontawesomeforeachfsfuturefuture.applygclusgenericsgeometryggplot2globalsgluegridExtragssgtableheatmaplyhighrhtmltoolshtmlwidgetshttrirlbaisobanditeratorsjquerylibjsonliteknitrlabelinglatentcorlaterlatticelazyevallifecyclelinproglistenvlpSolvemagicmagrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimemnormtmunsellmvtnormnlmenumDerivopensslparallellypcaPPpermutepillarpkgconfigplotlyplyrprocessxpromisespspurrrqapquantregR6rappdirsRColorBrewerRcppRcppArmadilloRcppProgressregistryreshape2rlangrmarkdownrngtoolssassscalesseriationsnSparseMspatialstablediststringistringrsurvivalsystibbletidyrtidyselecttimeDatetimeSeriestinytexTSPutf8vctrsveganviridisviridisLitewebshotwithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Construct a correlation matrix | autocor blockcor CorrStructure |
| Estimate latent correlation matrix | estimateR estimateR_mixed |
| Internal mixedCCA function finding w1 and w2 given R1, R2 and R12 | find_w12bic |
| Mixed type simulation data generator for sparse CCA | GenerateData |
| Kendall's tau correlation | KendallTau Kendall_matrix |
| Internal data-driven lambda sequence generating function. | lambdaseq_generate |
| Sparse CCA for data of mixed types with BIC criterion | mixedCCA |
| Internal RidgeCCA function | myrcc |
| Internal standard CCA function. | standardCCA |
