Package: circhelp 1.1.2

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_1.1.2.tar.gz
circhelp_1.1.2.zip(r-4.5)circhelp_1.1.2.zip(r-4.4)circhelp_1.1.2.zip(r-4.3)
circhelp_1.1.2.tgz(r-4.4-any)circhelp_1.1.2.tgz(r-4.3-any)
circhelp_1.1.2.tar.gz(r-4.5-noble)circhelp_1.1.2.tar.gz(r-4.4-noble)
circhelp_1.1.2.tgz(r-4.4-emscripten)circhelp_1.1.2.tgz(r-4.3-emscripten)
circhelp.pdf |circhelp.html✨
circhelp/json (API)
NEWS

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

Peer review:

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

Datasets:

On CRAN:

4.85 score 1 stars 6 scripts 235 downloads 31 exports 35 dependencies

Last updated 2 months agofrom:f3b9abdcaa. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 03 2024
R-4.5-winOKNov 03 2024
R-4.5-linuxOKNov 03 2024
R-4.4-winOKNov 03 2024
R-4.4-macOKNov 03 2024
R-4.3-winOKNov 03 2024
R-4.3-macOKNov 03 2024

Exports:angle_diff_180angle_diff_180_45angle_diff_360angle_diff_360_90angle_diff_90angle_diff_radcirc_corrcirc_descrcirc_lin_corrcirc_loesscirc_mean_180circ_mean_360circ_mean_radcirc_sd_180circ_sd_360circ_sd_radcorrect_angle_raddensity_asymmetrydensity_asymmetry_discretepad_circremove_cardinal_biasesremove_cardinal_biases_discretevm_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:clicolorspacedata.tablefansifarvergamlssgamlss.datagamlss.distggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSmathjaxrMatrixmgcvmunsellnlmepatchworkpillarpkgconfigR6RColorBrewerrlangscalessurvivaltibbleutf8vctrsviridisLitewithr

Correcting for cardinal biases to improve serial dependence estimates

Rendered fromcardinal_biases.Rmdusingknitr::rmarkdownon Nov 03 2024.

Last update: 2024-09-04
Started: 2022-01-03

Estimating serial dependence with density_asymmetry()

Andrey Chetverikov

Rendered fromserial_dependence_with_density_asymmetry.Rmdusingknitr::rmarkdownon Nov 03 2024.

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

Readme and manuals

Help Manual

Help pageTopics
Differences between angles in different circular spacesangle_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_180 circ_mean_360 circ_mean_rad
Circular standard deviationcirc_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
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