Package: HDANOVA 0.8.5

Kristian Hovde Liland

HDANOVA: High-Dimensional Analysis of Variance

Functions and datasets to support Smilde, Marini, Westerhuis and Liland (2025, ISBN: 978-1-394-21121-0) "Analysis of Variance for High-Dimensional Data - Applications in Life, Food and Chemical Sciences". This implements and imports a collection of methods for HD-ANOVA data analysis with common interfaces, result- and plotting functions, multiple real data sets and four vignettes covering a range different applications.

Authors:Kristian Hovde Liland [aut, cre]

HDANOVA_0.8.5.tar.gz
HDANOVA_0.8.5.zip(r-4.7-x86_64)HDANOVA_0.8.5.zip(r-4.7-arm64)HDANOVA_0.8.5.zip(r-4.6-x86_64)HDANOVA_0.8.5.zip(r-4.6-arm64)
HDANOVA_0.8.5.tar.gz(r-4.7-arm64)HDANOVA_0.8.5.tar.gz(r-4.7-x86_64)HDANOVA_0.8.5.tar.gz(r-4.6-arm64)HDANOVA_0.8.5.tar.gz(r-4.6-x86_64)
HDANOVA_0.8.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
HDANOVA/json (API)

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

Bug tracker:https://github.com/khliland/hdanova/issues

Pkgdown/docs site:https://khliland.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • caldana - Arabidopsis thaliana growth experiment
  • candies - Sensory assessment of candies.

On CRAN:

Conda:

openblascpp

4.08 score 2 packages 434 downloads 38 exports 82 dependencies

Last updated from:b204656bbb. Checks:9 OK, 1 ERROR. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK138
linux-devel-x86_64OK185
source / vignettesERROR290
linux-release-arm64OK184
linux-release-x86_64OK179
windows-devel-arm64OK242
windows-devel-x86_64OK249
windows-release-arm64OK251
windows-release-x86_64OK191
wasm-releaseOK121

Exports:apcaaplsascablock.data.framecoefplotcvsegmentsdummycodeextended.model.frameextract_estimateshdanovalimmpcaloading.weightsloadingplotloadingsmscaMSEPmvrValstatspcanovapcrpermanovapermutationpermutationplotplsplsrprcpredplotprojectionsR2RMSEProtationrotationplotscascoreplotscoressignfliptimeplotupdate_without_factorvalidationplot

Dependencies:abindbackportsbootbroomcarcarDataclicodetoolscolorspacecowplotcpp11crayonDerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegtablehmsisobandlabelinglatticeleapslifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvminqamixlmmodelrmultcompmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplspracmaprettyunitsprogresspurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangRSpectraS7sandwichscalesSparseMstringistringrsurvivalTH.datatibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

C. ASCA
Analysis of Variance Simultaneous Component Analysis (ASCA) | HDANOVA | Basic ASCA | Permutation testing | Random effects | Scores and loadings | Data ellipsoids and confidence ellipsoids | Combined effects | Quantitative effects | ANOVA-PCA (APCA) | PC-ANOVA | MSCA | LiMM-PCA | Repeated measures
Rendered fromvignette_C_ASCA.Rmdusingknitr::rmarkdown

Last update: 2025-08-30
Started: 2024-10-16

B. Analysis of Variance
Analysis of Variance (ANOVA) | Simulated data | Fixed effect models | One-way ANOVA | Two-way crossed effects ANOVA | Types of sums of squares | Contrast codings | Covariates in ANOVA | Fixed effect nested ANOVA | Linear mixed models | Classical - mixlm | Restrictions | Repeated Measures | REML | Multivariate ANOVA (MANOVA)
Rendered fromvignette_B_ANOVA.Rmdusingknitr::rmarkdown

Last update: 2025-01-21
Started: 2024-10-16

A. Data handling
Read from file | Data pre-processing | Re-coding categorical data | Data structures for analysis including blocks | Create list of blocks | Create data.frame of blocks
Rendered fromvignette_A_data.Rmdusingknitr::rmarkdown

Last update: 2024-10-16
Started: 2024-10-16

D. Additional methods
Additional methods of HD-ANOVA | Principal Response Curves (PRC) | Permutation Based MANOVA (PERMANOVA)
Rendered fromvignette_D_additional.Rmdusingknitr::rmarkdown

Last update: 2024-10-16
Started: 2024-10-16

Readme and manuals

Help Manual

Help pageTopics
ANOVA Principal Component Analysis - APCAapca
Analysis of Variance Partial Least Squares - APLSapls
Analysis of Variance Simultaneous Component Analysis - ASCAasca
ASCA Plot Methodsasca_plots loadingplot.asca permutationplot rotationplot scoreplot.asca
ASCA Result Methodsasca_results loadings.asca print.asca print.hdanova print.summary.asca print.summary.hdanova projections projections.asca scores.asca summary.asca summary.hdanova
Biplot for ASCA modelsbiplot.asca
Block-wise indexable data.frameblock.data.frame
Arabidopsis thaliana growth experimentcaldana
Sensory assessment of candies.candies
Dummy-coding of a single vectordummycode
Extracting the Extended Model Frame from a Formula or Fitextended.model.frame
Extract estimates for a given factor combinationextract_estimates
High-Dimensional Analysis of Variancehdanova
Linear Mixed Model PCAlimmpca
Model Frame and Model Matrix for ASCA-like Modelsmodel.frame.asca model.matrix.asca
Multilevel Simultaneous Component Analysis - MSCAmsca
Principal Components Analysis of Variance Simultaneous Component Analysis - PC-ANOVApcanova
PC-ANOVA Result Methodsloadingplot.pcanova pcanova_plots scoreplot.pcanova
PC-ANOVA Result Methodspcanova_results print.pcanova print.summary.pcanova projections.pcanova summary.pcanova
Permutation Based MANOVA - PERMANOVApermanova
Permutation for HDANOVApermutation
Partial Least Squares (PLS) for HDANOVApls pls.default
Principal Response Curvesprc
Rotation test for HDANOVArotation
Simultaneous Component Analysissca
Flip signs of a component/factor combination in a SCA/PCA objectsignflip
Timeplot for Combined Effectstimeplot
Update a Model without Factorupdate_without_factor