This package is considered a duplicate. The official version of this package is found at:https://khliland.r-universe.dev/HDANOVA

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.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✨
card.svg |card.png
HDANOVA/json (API)
NEWS

# 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:

openblas cpp

4.61 score 2 packages 17 scripts 619 downloads 38 exports 83 dependencies

Last updated from:b204656bbb. Checks:5 OK, 1 ERROR. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	164
linux-devel-x86_64	OK	208
source / vignettes	ERROR	255
linux-release-arm64	OK	187
linux-release-x86_64	OK	176
wasm-release	OK	131

Exports:apca apls asca block.data.frame coefplot cvsegments dummycode extended.model.frame extract_estimates hdanova limmpca loading.weights loadingplot loadings msca MSEP mvrValstats pcanova pcr permanova permutation permutationplot pls plsr prc predplot projections R2 RMSEP rotation rotationplot sca scoreplot scores signflip timeplot update_without_factor validationplot

Dependencies:abind backports boot broom car carData cli codetools colorspace cowplot cpp11 crayon Deriv doBy dplyr farver forecast Formula fracdiff generics ggplot2 glue gtable hms isoband labeling lattice leaps lifecycle lme4 lmtest magrittr MASS Matrix MatrixModels mgcv microbenchmark minqa mixlm modelr multcomp mvtnorm nlme nloptr nnet numDeriv pbkrtest pillar pkgconfig pls pracma prettyunits progress purrr quantreg R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen Rdpack reformulas rlang RSpectra S7 sandwich scales SparseM stringi stringr survival TH.data tibble tidyr tidyselect timeDate urca utf8 vctrs viridisLite withr zoo

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

A. Data handling

Rendered fromvignette_A_data.Rmdusingknitr::rmarkdownon May 29 2026.

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

B. Analysis of Variance

Rendered fromvignette_B_ANOVA.Rmdusingknitr::rmarkdownon May 29 2026.

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

C. ASCA

Rendered fromvignette_C_ASCA.Rmdusingknitr::rmarkdownon May 29 2026.

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

D. Additional methods

Rendered fromvignette_D_additional.Rmdusingknitr::rmarkdownon May 29 2026.

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

Help page	Topics
ANOVA Principal Component Analysis - APCA	apca
Analysis of Variance Partial Least Squares - APLS	apls
Analysis of Variance Simultaneous Component Analysis - ASCA	asca
ASCA Plot Methods	asca_plots loadingplot.asca permutationplot rotationplot scoreplot.asca
ASCA Result Methods	asca_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 models	biplot.asca
Block-wise indexable data.frame	block.data.frame
Arabidopsis thaliana growth experiment	caldana
Sensory assessment of candies.	candies
Dummy-coding of a single vector	dummycode
Extracting the Extended Model Frame from a Formula or Fit	extended.model.frame
Extract estimates for a given factor combination	extract_estimates
High-Dimensional Analysis of Variance	hdanova
Linear Mixed Model PCA	limmpca
Model Frame and Model Matrix for ASCA-like Models	model.frame.asca model.matrix.asca
Multilevel Simultaneous Component Analysis - MSCA	msca
Principal Components Analysis of Variance Simultaneous Component Analysis - PC-ANOVA	pcanova
PC-ANOVA Result Methods	loadingplot.pcanova pcanova_plots scoreplot.pcanova
PC-ANOVA Result Methods	pcanova_results print.pcanova print.summary.pcanova projections.pcanova summary.pcanova
Permutation Based MANOVA - PERMANOVA	permanova
Permutation for HDANOVA	permutation
Partial Least Squares (PLS) for HDANOVA	pls pls.default
Principal Response Curves	prc
Rotation test for HDANOVA	rotation
Simultaneous Component Analysis	sca
Flip signs of a component/factor combination in a SCA/PCA object	signflip
Timeplot for Combined Effects	timeplot
Update a Model without Factor	update_without_factor

Package: HDANOVA 0.8.5

HDANOVA: High-Dimensional Analysis of Variance

A. Data handling

B. Analysis of Variance

C. ASCA

D. Additional methods

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)