Bayesian Statistics for 2D/3D Transformations
Checks for validity of values for use as exponential distribution para...
Checks for validity of values for use as normal distribution parameter...
Checks validity of variables' matrix
Computes mean and optional quantiles for a coefficient.
Posterior distributions for transformation coefficients in full or sum...
Fitting Bidimensional or Tridimensional Regression / Geometric Transfo...
Fitting Bidimensional or Tridimensional Regression / Geometric Transfo...
Returns number of free matrix parameters in addition to translation
Checks if argument is a tridim_transformation object
Computes an efficient approximate leave-one-out cross-validation via l...
2D Affine
2D Euclidean
2D Projective
2D Translation Matrix
3D Affine
3D Euclidean, rotation about x
3D Euclidean, rotation about y
3D Euclidean, rotation about z
3D Projective
3D Translation Matrix
Posterior interval plots for key parameters. Uses bayesplot::mcmc_inte...
Computes posterior samples for the posterior predictive distribution.
Prints out tridim_transformation object
Computes R-squared using Bayesian R-squared approach. For detail refer...
Summary for a tridim_transformation object
Transformation matrix, 2D or 3D depending on data and transformation t...
Class tridim_transformation.
The 'TriDimRegression' package.
Computes mean and optional probabilities for a given variable.
Computes widely applicable information criterion (WAIC).
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>).
Useful links