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.
Package details |
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Author | Niklas Pfister and Jonas Peters |
Maintainer | Niklas Pfister <pfister@stat.math.ethz.ch> |
License | GPL-3 |
Version | 1.1 |
Package repository | View on CRAN |
Installation |
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