getQuantileRegion_4D: Multiple-output Bayesian quantile regression model

In brsantos/baquantreg: Bayesian quantile regression methods

Multiple-output Bayesian quantile regression model

Description

This function draws plots of the quantile region based on multiple-output quantile regression models, when the response variable has 4 dimensions.

Usage

getQuantileRegion_4D(
  model,
  datafile,
  response,
  ngridpoints = 100,
  xValue = 1,
  path_folder = NULL,
  splines_part = FALSE,
  wValue = NULL,
  print_plot = TRUE,
  model_name = "bayesx.estim",
  name_var,
  adaptive_dir = FALSE,
  ...
)

Arguments

model	This is an object of the class multBQR, produced by a call to the multBayesQR function.
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.
adaptive_dir	If TRUE, then directions will take into account the marginal quantiles of each dimension of the response variable. Otherwise, the direction vector are created creating all possible combinations of points inside the interval [-1, 1] given the number of points directionPoint. The default is FALSE.
...	Other parameters for summary.multBQR.

Value

A ggplot with the quantile regions based on Bayesian quantile regression model estimates.

brsantos/baquantreg documentation built on Feb. 8, 2023, 8:18 a.m.