Package: TCIU 1.2.7
TCIU: Spacekime Analytics, Time Complexity and Inferential Uncertainty
Provide the core functionality to transform longitudinal data to complex-time (kime) data using analytic and numerical techniques, visualize the original time-series and reconstructed kime-surfaces, perform model based (e.g., tensor-linear regression) and model-free classification and clustering methods in the book Dinov, ID and Velev, MV. (2021) "Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics", De Gruyter STEM Series, ISBN 978-3-11-069780-3. <https://www.degruyter.com/view/title/576646>. The package includes 18 core functions which can be separated into three groups. 1) draw longitudinal data, such as Functional magnetic resonance imaging(fMRI) time-series, and forecast or transform the time-series data. 2) simulate real-valued time-series data, e.g., fMRI time-courses, detect the activated areas, report the corresponding p-values, and visualize the p-values in the 3D brain space. 3) Laplace transform and kimesurface reconstructions of the fMRI data.
Authors:
TCIU_1.2.7.tar.gz
TCIU_1.2.7.tar.gz(r-4.5-noble)TCIU_1.2.7.tar.gz(r-4.4-noble)
TCIU_1.2.7.tgz(r-4.4-emscripten)TCIU_1.2.7.tgz(r-4.3-emscripten)
TCIU.pdf |TCIU.html✨
TCIU/json (API)
# Install 'TCIU' in R: |
install.packages('TCIU', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/socr/tciu/issues
- mask - Mask
- mask_dict - Mask_dict
- mask_label - Mask_label
- phase1_pval - Phase1_pval
- phase2_pval - Phase2_pval
- phase3_pval - Phase3_pval
- sample_save - Sample_save
Last updated 3 months agofrom:18fb0fdc05. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 15 2024 |
R-4.5-linux-x86_64 | OK | Nov 15 2024 |
Exports:fmri_2dvisualfmri_3dvisualfmri_3dvisual_regionfmri_imagefmri_kimesurfacefmri_post_hocfmri_pval_comparison_2dfmri_pval_comparison_3dfmri_ROI_phase1fmri_ROI_phase2fmri_simulate_funcfmri_stimulus_detectfmri_time_seriesfmri_ts_forecastGaussSmoothArrayGaussSmoothKernelILTinv_kimesurface_transformkimesurface_transformLT
Dependencies:abindaskpassawsawsMethodsbackportsbase64encbitopsbootbroombslibcachemcarcarDataclicodetoolscolorspacecorrplotcowplotcpp11crosstalkcubaturecurldata.tableDBIdeldirDEoptimRDerivdigestdoBydoParalleldplyrDTevaluateextraDistrfancycutfansifarverfastmapfmrifontawesomeforeachforecastFormulafracdifffsgenericsgeometryggplot2ggpubrggrepelggsciggsignifgluegoftestgridExtragslgtablehighrhtmltoolshtmlwidgetshttpuvhttrICSICSNPinterpisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelinproglme4lmtestlpSolvemagicmagrittrMASSmathjaxrMatrixMatrixModelsmemoisemetadatmetaformgcvmicrobenchmarkmimeminqamitoolsmodelrMultiwayRegressionmunsellmvtnormnlmenloptrnnetnumDerivopenssloro.niftipbapplypbkrtestpcaPPpillarpkgconfigplotlyplyrpolyclippolynompracmapromisespurrrquadprogquantmodquantregR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppProgressreshape2rlangrmarkdownRNiftirobustbaserrcovrstatixsassscalesSparseMspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrsurveysurvivalsystensortibbletidyrtidyselecttimeDatetinytextseriesTTRurcautf8vctrsviridisLitewithrxfunxtsyamlzoo
Laplace Transform and Kimesurface Transform of TCIU Analytics
Rendered fromtciu-LT-kimesurface.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2023-10-06
Started: 2020-08-27
Functions & Workflow of TCIU Analytics
Rendered fromtciu-fMRI-analytics.Rmd
usingknitr::rmarkdown
on Nov 15 2024.Last update: 2024-05-18
Started: 2020-08-27