CarbonExample1Data      Carbon, C. C. (2013), data set #1
CarbonExample2Data      Carbon, C. C. (2013), data set #2
CarbonExample3Data      Carbon, C. C. (2013), data set #3
EyegazeData             Eye gaze calibration data
Face3D_M010             Face landmarks, male, #010
Face3D_M101             Face landmarks, male, #101
Face3D_M244             Face landmarks, male, #244
Face3D_M92              Face landmarks, male, #092
Face3D_W070             Face landmarks, female, #070
Face3D_W097             Face landmarks, female, #097
Face3D_W182             Face landmarks, female, #182
Face3D_W243             Face landmarks, female, #243
FriedmanKohlerData1     Friedman & Kohler (2003), data set #1
FriedmanKohlerData2     Friedman & Kohler (2003), data set #2
NakayaData              Nakaya (1997)
R2                      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.
TriDimRegression-package
                        The 'TriDimRegression' package.
coef.tridim_transformation
                        Posterior distributions for transformation
                        coefficients in full or summarized form.
fit_transformation      Fitting Bidimensional or Tridimensional
                        Regression / Geometric Transformation Models
                        via Formula.
fit_transformation_df   Fitting Bidimensional or Tridimensional
                        Regression / Geometric Transformation Models
                        via Two Tables.
is.tridim_transformation
                        Checks if argument is a 'tridim_transformation'
                        object
loo.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.
plot.tridim_transformation
                        Posterior interval plots for key parameters.
                        Uses bayesplot::mcmc_intervals.
predict.tridim_transformation
                        Computes posterior samples for the posterior
                        predictive distribution.
print.tridim_transformation
                        Prints out tridim_transformation object
summary.tridim_transformation
                        Summary for a tridim_transformation object
tridim_transformation-class
                        Class 'tridim_transformation'.
waic.tridim_transformation
                        Computes widely applicable information
                        criterion (WAIC).
