Package: TriDimRegression 1.0.1

TriDimRegression: Bayesian Statistics for 2D/3D Transformations

Fits 2D and 3D geometric transformations via 'Stan' probabilistic programming engine ( Stan Development Team (2021) <https://mc-stan.org>). Returns posterior distribution for individual parameters of the fitted distribution. Allows for computation of LOO and WAIC information criteria (Vehtari A, Gelman A, Gabry J (2017) <doi:10.1007/s11222-016-9696-4>) as well as Bayesian R-squared (Gelman A, Goodrich B, Gabry J, and Vehtari A (2018) <doi:10.1080/00031305.2018.1549100>).

Authors:Alexander Pastukhov [aut, cre], Claus-Christian Carbon [aut]

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TriDimRegression.pdf |TriDimRegression.html✨
TriDimRegression/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/alexander-pastukhov/tridim-regression/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

bidimensional-regressiontridimenisional-regression

4.18 score 7 scripts 159 downloads 21 exports 71 dependencies

Last updated 1 years agofrom:7a9dcf4e33. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-win-x86_64NOTEOct 26 2024
R-4.5-linux-x86_64NOTEOct 26 2024
R-4.4-win-x86_64NOTEOct 26 2024
R-4.4-mac-x86_64NOTEOct 26 2024
R-4.4-mac-aarch64NOTEOct 26 2024
R-4.3-win-x86_64NOTEOct 26 2024
R-4.3-mac-x86_64NOTEOct 26 2024
R-4.3-mac-aarch64NOTEOct 26 2024

Exports:check_exponential_priorcheck_normal_priorcheck_variablescoef_summaryfit_transformationfit_transformation_dfget_beta_nis.tridim_transformationm2_affinem2_euclideanm2_projectivem2_translationm3_affinem3_euclidean_xm3_euclidean_ym3_euclidean_zm3_projectivem3_translationR2transformation_matrixvariable_summary

Dependencies:abindbackportsbayesplotBHcallrcheckmateclicodetoolscolorspacecpp11descdigestdistributionaldplyrfansifarverFormulafuturegenericsggplot2ggridgesglobalsgluegridExtragtableinlineisobandlabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstanrstantoolsscalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr

Comparing faces

Alexander (Sasha) Pastukhov

Rendered fromcomparing_faces.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-01-14
Started: 2021-03-19

Eye gaze mapping

Alexander (Sasha) Pastukhov

Rendered fromcalibration.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2022-01-14
Started: 2020-10-12

Transformation matrices

Alexander (Sasha) Pastukhov

Rendered fromtransformation_matrices.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2021-10-05
Started: 2021-03-19

Readme and manuals

Help Manual

Help pageTopics
The 'TriDimRegression' package.TriDimRegression-package TriDimRegression
Carbon, C. C. (2013), data set #1CarbonExample1Data
Carbon, C. C. (2013), data set #2CarbonExample2Data
Carbon, C. C. (2013), data set #3CarbonExample3Data
Posterior distributions for transformation coefficients in full or summarized form.coef.tridim_transformation
Eye gaze calibration dataEyegazeData
Face landmarks, male, #010Face3D_M010
Face landmarks, male, #101Face3D_M101
Face landmarks, male, #244Face3D_M244
Face landmarks, male, #092Face3D_M92
Face landmarks, female, #070Face3D_W070
Face landmarks, female, #097Face3D_W097
Face landmarks, female, #182Face3D_W182
Face landmarks, female, #243Face3D_W243
Fitting Bidimensional or Tridimensional Regression / Geometric Transformation Models via Formula.fit_transformation fit_transformation.formula
Fitting Bidimensional or Tridimensional Regression / Geometric Transformation Models via Two Tables.fit_transformation_df
Friedman & Kohler (2003), data set #1FriedmanKohlerData1
Friedman & Kohler (2003), data set #2FriedmanKohlerData2
Checks if argument is a 'tridim_transformation' objectis.tridim_transformation
Computes an efficient approximate leave-one-out cross-validation via loo library. It can be used for a model comparison via loo::loo_compare() function.loo.tridim_transformation
Nakaya (1997)NakayaData
Posterior interval plots for key parameters. Uses bayesplot::mcmc_intervals.plot.tridim_transformation
Computes posterior samples for the posterior predictive distribution.predict.tridim_transformation
Prints out tridim_transformation objectprint.tridim_transformation
Computes R-squared using Bayesian R-squared approach. For detail refer to: Andrew Gelman, Ben Goodrich, Jonah Gabry, and Aki Vehtari (2018). R-squared for Bayesian regression models. The American Statistician, doi:10.1080/00031305.2018.1549100.R2 R2.tridim_transformation
Summary for a tridim_transformation objectsummary.tridim_transformation
Class 'tridim_transformation'.tridim_transformation tridim_transformation-class
Computes widely applicable information criterion (WAIC).waic.tridim_transformation