Package: TPLSr 1.0.5

TPLSr: Thresholded Partial Least Squares Model for Neuroimaging Data

Uses thresholded partial least squares algorithm to create a regression or classification model. For more information, see Lee, Bradlow, and Kable <doi:10.1016/j.crmeth.2022.100227>.

Authors:Sangil Lee [aut, cre]

TPLSr_1.0.5.tar.gz
TPLSr_1.0.5.zip(r-4.7)TPLSr_1.0.5.zip(r-4.6)TPLSr_1.0.5.zip(r-4.5)
TPLSr_1.0.5.tgz(r-4.6-any)TPLSr_1.0.5.tgz(r-4.5-any)
TPLSr_1.0.5.tar.gz(r-4.7-any)TPLSr_1.0.5.tar.gz(r-4.6-any)
TPLSr_1.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
TPLSr/json (API)
NEWS

# Install 'TPLSr' in R:
install.packages('TPLSr', repos = c('https://sangillee.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sangillee/tplsr/issues

Datasets:
  • TPLSdat - Sample participant data from a left-right button press task

On CRAN:

Conda:

4.00 score 4 scripts 194 downloads 6 exports 64 dependencies

Last updated from:1b50f25b57. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK155
source / vignettesOK260
linux-release-x86_64OK156
macos-release-arm64OK202
macos-oldrel-arm64OK239
windows-develOK104
windows-releaseOK101
windows-oldrelOK112
wasm-releaseOK139

Exports:evalTuningParammakePredictorplotTuningSurfaceTPLSTPLS_cvTPLSpredict

Dependencies:askpassbase64encbslibcachemclicpp11crosstalkcurldata.tabledigestdplyrevaluatefarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonliteknitrlabelinglaterlazyevallifecyclemagrittrmemoisemimeopensslotelpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcpprlangrmarkdownS7sassscalesstringistringrsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

TPLS_example1

Rendered fromTPLS_example1.Rmdusingknitr::rmarkdownon May 18 2026.

Last update: 2022-06-13
Started: 2022-06-13

TPLS_example2

Rendered fromTPLS_example2.Rmdusingknitr::rmarkdownon May 18 2026.

Last update: 2022-06-13
Started: 2022-06-13