ice.areg: ICE plot for the alpha-regression

In CompositionalSR: Spatial Regression Models with Compositional Data

ICE plot for the \alpha-regression

Description

ICE plot for the \alpha-regression.

Usage

ice.areg(be, x, ind = 1, frac = 0.25, pos = 0.5)

Arguments

be	A numerical matrix with the estimated \alpha-regression coefficients.
x	A numerical matrix with the predictor variables.
ind	Which variable to select?.
frac	Fraction of observations to use. The default value is 0.25.
pos	This is a number between 0 and 1 and is used to place the legend in the appropriate place.

Details

This function implements the Individual Conditional Expecation plots of Goldstein et al. (2015). See the references for more details.

Value

A graph with several curves, one for each component. The horizontal axis contains the selected variable, whereas the vertical axis contains the locally smoothed predicted compositional lines.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

https://christophm.github.io/interpretable-ml-book/ice.html

Goldstein, A., Kapelner, A., Bleich, J. and Pitkin, E. (2015). Peeking inside the black box: Visualizing statistical learning with plots of individual conditional expectation. Journal of Computational and Graphical Statistics 24(1): 44-65.

See Also

areg, cv.alfareg

Examples

data(fadn)
y <- fadn[, 3:7]
x <- fadn[, 8, drop = FALSE]
mod <- alfa.reg(y, x, 0.2)
ice <- ice.areg(mod$be, x, ind = 1)

CompositionalSR documentation built on March 28, 2026, 5:07 p.m.