Package: seqICP
Title: Sequential Invariant Causal Prediction
Version: 1.1
Author: Niklas Pfister and Jonas Peters
Maintainer: Niklas Pfister <pfister@stat.math.ethz.ch>
Description: Contains an implementation of invariant causal prediction for sequential data. The main function in the package is 'seqICP', which performs linear sequential invariant causal prediction and has guaranteed type I error control. For non-linear dependencies the package also contains a non-linear method 'seqICPnl', which allows to input any regression procedure and performs tests based on a permutation approach that is only approximately correct. In order to test whether an individual set S is invariant the package contains the subroutines 'seqICP.s' and 'seqICPnl.s' corresponding to the respective main methods.
Depends: R (>= 3.2.3)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dHSIC, mgcv, stats
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-25 11:32:46 UTC; pfisteni
Repository: CRAN
Date/Publication: 2017-07-25 14:54:20 UTC
Built: R 4.6.0; ; 2026-04-26 04:49:20 UTC; unix
