Package: circhelp 1.4.0

Andrey Chetverikov

circhelp: Circular Analyses Helper Functions

Light-weight functions for computing descriptive statistics in different circular spaces (e.g., 2pi, 180, or 360 degrees), to handle angle-dependent biases, pad circular data, and more. Specifically aimed for psychologists and neuroscientists analyzing circular data. Basic methods are based on Jammalamadaka and SenGupta (2001) <doi:10.1142/4031>, removal of cardinal biases is based on the approach introduced in van Bergen, Ma, Pratte, & Jehee (2015) <doi:10.1038/nn.4150> and Chetverikov and Jehee (2023) <doi:10.1038/s41467-023-43251-w>.

Authors:Andrey Chetverikov [aut, cre], Eline Van Geert [ctb]

circhelp_1.4.0.tar.gz
circhelp_1.4.0.zip(r-4.7-any)circhelp_1.4.0.zip(r-4.6-any)circhelp_1.4.0.zip(r-4.5-any)
circhelp_1.4.0.tgz(r-4.6-any)circhelp_1.4.0.tgz(r-4.5-any)
circhelp_1.4.0.tar.gz(r-4.7-any)circhelp_1.4.0.tar.gz(r-4.6-any)
circhelp_1.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
circhelp/json (API)

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

Bug tracker:https://github.com/achetverikov/circhelp/issues

Datasets:

On CRAN:

Conda:

4.70 score 1 stars 10 scripts 325 downloads 35 exports 21 dependencies

Last updated from:bf47ec96ac. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK143
source / vignettesOK187
linux-releaseOK187
macos-releaseOK129
macos-oldrelOK126
windows-develOK115
windows-releaseOK87
windows-oldrelOK109
wasm-releaseOK105

Exports:angle_diffangle_diff_180angle_diff_180_45angle_diff_360angle_diff_360_90angle_diff_90angle_diff_radcirc_corrcirc_descrcirc_lin_corrcirc_loesscirc_meancirc_mean_180circ_mean_360circ_mean_radcirc_sdcirc_sd_180circ_sd_360circ_sd_radcorrect_angle_raddensity_asymmetrydensity_asymmetry_discretepad_circremove_cardinal_biasesremove_cardinal_biases_discretesmoothed_circ_sdvm_circ_sd_deg_to_kappavm_circ_sd_to_kappavm_kappa_to_circ_sdvm_kappa_to_circ_sd_degweighted_circ_meanweighted_circ_mean2weighted_circ_rhoweighted_circ_sdweighted_sem

Dependencies:clicpp11data.tablefarverggplot2gluegtableisobandlabelinglifecycleMASSmathjaxrpatchworkR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

Correcting for cardinal biases to improve serial dependence estimates
Rendered fromcardinal_biases.Rmdusingknitr::rmarkdown

Last update: 2026-10-04
Started: 2022-01-03

Estimating serial dependence with density_asymmetry()
Rendered fromserial_dependence_with_density_asymmetry.Rmdusingknitr::rmarkdown

Last update: 2026-10-04
Started: 2024-09-04

Readme and manuals

Help Manual

Help pageTopics
Differences between angles in different circular spacesangle_diff angle_diff_180 angle_diff_180_45 angle_diff_360 angle_diff_360_90 angle_diff_90 angle_diff_rad
Data from a motion estimation taskBae_Luck_2018_data
Circular correlation coefficientcirc_corr
A set of descriptive statistics for circular datacirc_descr
Circular-linear correlationcirc_lin_corr
An implementation of circular-linear locally-weighted regression (LOESS)circ_loess
Circular meancirc_mean circ_mean_180 circ_mean_360 circ_mean_rad
Circular standard deviationcirc_sd circ_sd_180 circ_sd_360 circ_sd_rad
Get angle value in [-pi, pi] spacecorrect_angle_rad
Compute asymmetry in weighted probability densitydensity_asymmetry
Compute asymmetry in weighted probability density for discrete datadensity_asymmetry_discrete
Pad circular data on both endspad_circ
Data from an orientation estimation taskPascucci_et_al_2019_data
Remove cardinal biasesremove_cardinal_biases
Remove cardinal biases for data with orientation (color, motion, ...) set in discrete stepsremove_cardinal_biases_discrete
Compute smoothed estimate of circular standard deviationsmoothed_circ_sd
Conversion between the circular SD and kappa of von Misesvm_circ_sd_deg_to_kappa vm_circ_sd_to_kappa vm_kappa_to_circ_sd vm_kappa_to_circ_sd_deg
Weighted circular parametersweighted_circ_mean weighted_circ_mean2 weighted_circ_rho weighted_circ_sd
Weighted standard error of the mean (SEM_w)weighted_sem