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seqICP

Sequential Invariant Causal Prediction

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.

Versions across snapshots

VersionRepositoryFileSize
1.1 rolling linux/jammy R-4.5 seqICP_1.1.tar.gz 95.3 KiB
1.1 rolling linux/noble R-4.5 seqICP_1.1.tar.gz 95.3 KiB
1.1 rolling source/ R- seqICP_1.1.tar.gz 23.2 KiB
1.1 latest linux/jammy R-4.5 seqICP_1.1.tar.gz 95.3 KiB
1.1 latest linux/noble R-4.5 seqICP_1.1.tar.gz 95.3 KiB
1.1 latest source/ R- seqICP_1.1.tar.gz 23.2 KiB
1.1 2026-04-26 source/ R- seqICP_1.1.tar.gz 23.2 KiB
1.1 2026-04-23 source/ R- seqICP_1.1.tar.gz 23.2 KiB
1.1 2026-04-09 windows/windows R-4.5 seqICP_1.1.zip 97.7 KiB
1.1 2025-04-20 source/ R- seqICP_1.1.tar.gz 23.2 KiB

Dependencies (latest)

Imports