View source: R/drawQuantileRegion_3D.R
| drawQuantileRegion_3D | R Documentation | 
This function draws plots of the quantile region based on multiple-output quantile regression models, when the response variable has 3 dimensions.
drawQuantileRegion_3D(
  model,
  datafile,
  response,
  ngridpoints = 100,
  xValue = 1,
  path_folder = NULL,
  splines_part = FALSE,
  wValue = NULL,
  print_plot = TRUE,
  model_name = "bayesx.estim",
  name_var,
  ...
)
model | 
 This is an object of the class   | 
datafile | 
 A data.frame from which to find the variables defined in the formula.  | 
response | 
 Names of response variables  | 
ngridpoints | 
 Number of grid points considered to build this quantile region, where a thorough search will look for the specified region, given the estimates for several directions. Default is 100, that will produce a grid with 10.000 points in the observed range of the data.  | 
xValue | 
 Fixed value of the predictor variables. Default value is 1 when there is only the intercept. If there is the interest in comparing the quantile regions for different values of predictors, it must used with a list of values for the predictors.  | 
path_folder | 
 The path where all results are stored.  | 
splines_part | 
 Logical value to indicate whether there are splines terms in the equation to draw the quantile contours.  | 
wValue | 
 Fixed value to be plugged in the spline part of the equation.  | 
print_plot | 
 Logical determining whether plot should be printed or data with coordinantes should be returned. Only checked when paintedArea is FALSE. Default is TRUE.  | 
model_name | 
 When results will be collected in a folder, this should be the name of the name considered by BayesX to save all tables. Default is 'bayesx.estim'.  | 
name_var | 
 When there is a nonlinear variable from which one wants to consider different values for plotting, this should have the name of the variable.  | 
... | 
 Other parameters for   | 
A ggplot with the quantile regions based on Bayesian quantile regression model estimates.
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