Package: squat 0.5.0.9000

Aymeric Stamm

squat: Statistics for Quaternion Temporal Data

An implementation of statistical tools for the analysis of rotation-valued time series and functional data. It relies on pre-existing quaternion data structure provided by the 'Eigen' 'C++' library.

Authors:Lise Bellanger [aut], Pierre Drouin [aut], Aymeric Stamm [aut, cre], Benjamin Martineau [ctb]

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
squat/json (API)

# Install 'squat' in R:

install.packages('squat', repos = c('https://lmjl-alea.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lmjl-alea/squat/issues

Pkgdown/docs site:https://lmjl-alea.github.io

Uses libs:

c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

vespa - The VESPA dataset
vespa64 - The VESPA64 dataset

On CRAN:

cpp openmp

3.00 score 2 stars 7 scripts 290 downloads 32 exports 106 dependencies

Last updated from:b9e8d885ef. Checks:15 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	217
linux-devel-x86_64	OK	240
source / vignettes	OK	268
linux-release-arm64	OK	212
linux-release-x86_64	OK	272
macos-release-arm64	OK	284
macos-release-x86_64	OK	419
macos-oldrel-arm64	OK	273
macos-oldrel-x86_64	OK	368
windows-devel-arm64	OK	498
windows-devel-x86_64	OK	313
windows-release-arm64	OK	509
windows-release-x86_64	OK	210
windows-oldrel-x86_64	OK	234
wasm-release	OK	164

Exports:append as_qts as_qts_sample centring dbscan differentiate dist DTW hclust hemispherize inverse_qts is_qts is_qts_sample kmeans moving_average normalize qts2aamts qts2aats qts2aavts qts2ats qts2avmts qts2avvts qts2dts qts2nts qts2rpyts qts2sqts reorient resample rnorm_qts scale smooth straighten

Dependencies:abind askpass base64enc bslib cachem cli cluster coda codetools cpp11 crosstalk curl data.table dbscan DEoptimR digest doParallel dotCall64 dplyr dtw evaluate farver fastmap fdacluster fdasrvf fields fontawesome foreach fs funData future future.apply generics ggplot2 ggrepel globals glue gtable highr htmltools htmlwidgets httr irlba isoband iterators jquerylib jsonlite knitr labeling later lattice lazyeval lifecycle listenv lpSolve magrittr maps MASS Matrix memoise MFPCA mgcv mime minpack.lm mvtnorm nlme nloptr openssl otel parallelly pillar pkgconfig plotly plyr progressr promises proxy purrr R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen rlang rmarkdown roahd robustbase S7 sass scales spam stringi stringr sys tibble tidyr tidyselect tinytex tolerance utf8 vctrs viridisLite withr xfun yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Operator '-' for 'qts' Objects	-.qts
Operator '*' for 'qts' Objects	*.qts
Operator '+' for 'qts' Objects	+.qts
QTS Sample Concatenation	append append.default append.qts_sample
Plot for 'prcomp_qts' objects	autoplot.prcomp_qts
Plot for 'qts' objects	autoplot.qts
Plot for 'qts_sample' objects	autoplot.qts_sample
Plot for 'qtsclust' objects	autoplot.qtsclust
QTS Centering and Standardization	centring
QTS Nearest-Neighbor Clustering	dbscan dbscan.default dbscan.qts_sample
QTS Differentiation	differentiate differentiate.qts differentiate.qts_sample
QTS Distance Matrix Computation	dist dist.default dist.qts_sample
Dynamic Time Warping for Quaternion Time Series	DTW
QTS Exponential	exp exp.qts exp.qts_sample
QTS Hierarchical Agglomerative Clustering	hclust hclust.default hclust.qts_sample
QTS Hemispherization	hemispherize hemispherize.qts hemispherize.qts_sample
Inverse Operator for 'qts' Objects	inverse_qts
QTS K-Means Alignment Algorithm	kmeans kmeans.default kmeans.qts_sample
QTS Logarithm	log log.qts log.qts_sample
QTS Geometric Mean	mean.qts_sample
QTS Geometric Median	median.qts_sample
QTS Moving Average	moving_average moving_average.qts moving_average.qts_sample
QTS Normalization	normalize normalize.qts normalize.qts_sample
Plot for 'prcomp_qts' objects	plot.prcomp_qts screeplot.prcomp_qts
Plot for 'qts' objects	plot.qts
Plot for 'qts_sample' objects	plot.qts_sample
Plot for 'qtsclust' objects	plot.qtsclust
PCA for QTS Sample	prcomp.qts_sample
Predict QTS from PCA decomposition	predict.prcomp_qts
QTS Class	as_qts format.qts is_qts print.qts qts
QTS Sample Class	as_qts_sample is_qts_sample qts_sample [.qts_sample
QTS Transformation to Angular Acceleration Magnitude Time Series	qts2aamts
QTS Transformation to Angle-Axis Time Series	qts2aats
QTS Transformation to Angular Acceleration Vector Time Series	qts2aavts
QTS Transformation To Angle Time Series	qts2ats
QTS Transformation to Angular Velocity Magnitude Time Series	qts2avmts
QTS Transformation to Angular Velocity Vector Time Series	qts2avvts
QTS Transformation To Distance Time Series	qts2dts
QTS Transformation To Norm Time Series	qts2nts
QTS Transformation to Roll-Pitch-Yaw Time Series	qts2rpyts
QTS Transformation to Smoothed Quaternion Time Series	qts2sqts
QTS Reorientation	reorient reorient.qts reorient.qts_sample
QTS Resampling	resample resample.qts resample.qts_sample
QTS Random Sampling	rnorm_qts
QTS Sample Centering and Standardization	scale scale.default scale.qts_sample
QTS Smoothing via SLERP Interpolation	smooth smooth.default smooth.qts smooth.qts_sample
QTS Straightening	straighten straighten.qts straighten.qts_sample
The VESPA dataset	vespa
The VESPA64 dataset	vespa64