Method for Confidence Bands in JMP Residual Normal Quantile Plots Hello everyone, I’m curious about the statistical method used to generate the confidence bands in the residual normal quantile plot within JMP. Could anyone share the underlying approach, such as whether it’s based on parametric, nonparametric, or bootstrap methods? Any insights into the calculation principles or technical details would be greatly appreciated!
JMP PRO 17.1.0
Basic Data Analysis and ModelingRe: Method for Confidence Bands in JMP Residual Normal Quantile PlotsThese are my guesses
Plot Residuals ( Basic Analysis > Bivariate Analysis > Bivariate Platform Options > Bivariate Fit Options )
(Available for Linear, Polynomial, Passing Bablok, and Fit Special Only.) Shows or hides five diagnostic plots: residual by predicted, actual by predicted, residual by row, residual by X, and a normal quantile plot of the residuals.
Basic Analysis > Distributions > Options for Continuous Variables > Normal Quantile Plot (Conover, W. J. (1980). Practical Nonparametric Statistics. New York: John Wiley & Sons.)
or possibly Fitting Linear Models > Mixed Models > Marginal Model Inference > Residual Plots (Conover, W. J. (1999). Practical Nonparametric Statistics. 3rd ed. New York: John Wiley & Sons.)
