BCSreg (version 1.1.1)

envelope: Normal Probability Plots with Simulated Envelope for a Box-Cox Symmetric Regression Fit

Description

Produce the normal probability plot with simulated envelope of the quantile residuals obtained from a Box-Cox symmetric regression fit.

Usage

envelope(object, rep = 60, conf = 0.95, envcol, ...)

Value

envelope returns normal probability plot with simulated envelopes for the quantile residuals.

Arguments

object

a fitted model object of class "BCSreg".

rep

a positive integer representing the number of iterations to calculate the simulated envelopes. Default is rep = 60.

conf

a numeric value in the interval (0,1) that represents the confidence level of the simulated envelope. Default is conf = 0.95.

envcol

character specifying the color of the envelope.

...

additional graphical parameters (see par).

Author

Francisco F. de Queiroz <>

Rodrigo M. R. de Medeiros <>

Details

The envelope uses the idea of Atkinson (1985) to create normal probability plots with simulated envelope. Under the correct model, approximately 100 * conf of the residuals are expected to be inside the envelope.

Currently, the envelope() function, when used in a zero-adjusted Box-Cox symmetric regression fit, returns only the quantile plot for the quantile residuals obtained under a combined approach (see residuals.BCSreg).

References

Atkinson, A. C. (1985). Plots, Transformations and Regression: An Introduction to Graphical Methods of Diagnostic Regression Analysis. Oxford Science Publications, Oxford.

Medeiros, R. M. R., and Queiroz, F. F. (2025). Flexible modeling of nonnegative continuous data: Box-Cox symmetric regression and its zero-adjusted extension.

See Also

BCSreg, residuals.BCSreg

Examples

## Data set: raycatch (for description, run ?raycatch)
hist(raycatch$cpue, xlab = "Catch per unit effort")
plot(cpue ~ tide_phase, raycatch, pch = 16,
   xlab = "Tide phase", ylab = "Catch per unit effort")
plot(cpue ~ location, raycatch, pch = 16,
   xlab = "Location", ylab = "Catch per unit effort")
plot(cpue ~ max_temp, raycatch, pch = 16,
   xlab = "Maximum temperature", ylab = "Catch per unit effort")

## Fit a double Box-Cox normal regression model:
fit <- BCSreg(cpue ~ location + tide_phase |
               location + tide_phase + max_temp, raycatch)
envelope(fit)