Conditional Multivariate Reference Regions
Alternating Conditional Expectation (ACE) algorithm
Bivariate reference region estimation
Bivariate regression model
Kernel bandwidth selection method based on bivariate density contours ...
Plot a bivRegion object
Plot method for bivRegr fit
Plot univariate conditional quantile models curves (i.e. reference cur...
Default summary_boot plotting
Default trivRegion plotting
Prediction for a bivRegion object
Predict method for bivRegr
Univariate reference curve model
bivRegion summary method
bivRegr summary function
Trivariate reference region estimation
Trivariate regression model
An R package for estimating conditional multivariate reference regions. The reference region is non parametrically estimated using a kernel density estimator. Covariates effects on the multivariate response means vector and variance-covariance matrix, thus on the region shape, are estimated by flexible additive predictors. Continuous covariates non linear effects might be estimated using penalized splines smoothers. Confidence intervals for the covariates estimated effects might be derived from bootstrap resampling. Kernel density bandwidth can be estimated with different methods, including a method that optimize the region coverage. Numerical, and graphical, summaries can be obtained by the user in order to evaluate reference region performance with real data. Full mathematical details can be found in <doi:10.1002/sim.9163> and <doi:10.1007/s00477-020-01901-1>.