confint.TSVC: Confidence intervals for Varying Coefficient Trees

In TSVC: Tree-Structured Modelling of Varying Coefficients

Confidence intervals for Varying Coefficient Trees

Description

Construct parametric bootstrap percentile confidence intervals of effects of covariates that vary with the values of one or several effect modifiers. The basic method is described in Spuck et al. (2025).

Usage

## S3 method for class 'TSVC'
confint(
  object,
  bootstrap_n = 500,
  alpha = 0.05,
  post_pruning = NULL,
  splits_max = 5,
  trace = FALSE,
  ...
)

Arguments

object	a fitted object of class TSVC.
bootstrap_n	the number of bootstrap samples to be drawn.
alpha	significance level alpha of the confidence interval.
post_pruning	method to select the maximal number of splits; can be "AIC" or "BIC". If NULL (default), no post-pruning is performed.
splits_max	maximal number of splits to be considered. If post_pruning is NULL it is ignored.
trace	if TRUE, information about the estimation progress is printed.
...	further arguments passed to or from other methods.

Details

The method is so far mainly put to the test for gaussian (family=gaussian) and binary (family=binary(link="logit")) outcome. It should be taken with care for differently scaled outcomes.

Author(s)

Moritz Berger <[e-mail]>
https://www.imbie.uni-bonn.de/people/dr-moritz-berger/

Nikolai Spuck <[e-mail]>
https://www.imbie.uni-bonn.de/people/nikolai-spuck/

References

Berger, M., G. Tutz and M. Schmid (2019). Tree-Structured Modelling of Varying Coefficients. Statistics and Computing 29, 217-229, https://doi.org/10.1007/s11222-018-9804-8.

Spuck, N., M. Schmid, M. Monin and M. Berger (2025). Confidence intervals for tree-structured varying coefficients. Computational Statistics and Data Analysis.

See Also

TSVC, plot.TSVC, predict.TSVC, summary.TSVC

Examples

# Swiss Labour Market 
library(AER)
data("SwissLabor")

# recode factors 
sl <- SwissLabor
sl$participation <- as.numeric(sl$participation)-1
sl$foreign       <- as.numeric(sl$foreign)-1

## Not run: 
fit1 <- TSVC(participation~income+age, data=sl, family=binomial(link="logit"), 
perm_test=FALSE, test_linear=FALSE, splits_max=3)
confint(fit1, bootstrap_n=500, alpha=0.05, trace=TRUE)

## End(Not run)

TSVC documentation built on April 3, 2025, 10:26 p.m.