.quantilePercentiles {JWileymisc} | R Documentation |
Internal Function to Calculate Quantiles
Description
Function calculates smoothing spline quantiles or linear quantiles as a fall back. Not intended for general use. Expected predicted and residual data. Exported to support related packages.
Usage
.quantilePercentiles(
data,
Mid = 0.5,
LL = 0.1,
UL = 0.9,
na.rm = TRUE,
cut = 8L
)
Arguments
data |
A dataset of predicted and residual values. Assumed from some sort of (probably parametric) model. |
Mid |
The middle limit for prediction. Defaults to
|
LL |
The lower limit for prediction. Defaults to
|
UL |
The upper limit for prediction. Defaults to
|
na.rm |
A logical whether to remove missing values.
Defaults to |
cut |
An integer, how many unique predicted values there have to be at least for it to use quantile regression or treat the predicted values as discrete. Defaults to 8. |
Value
A data.table with the scores and predicted LL and UL, possibly missing if quantile regression models do not converge.