Package: seqICP 1.1
Niklas Pfister
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.
Authors:
seqICP_1.1.tar.gz
seqICP_1.1.tar.gz(r-4.5-noble)seqICP_1.1.tar.gz(r-4.4-noble)
seqICP_1.1.tgz(r-4.4-emscripten)seqICP_1.1.tgz(r-4.3-emscripten)
seqICP.pdf |seqICP.html✨
seqICP/json (API)
| # Install 'seqICP' in R: |
| install.packages('seqICP', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 8 years agofrom:ab9791c1b5. Checks:3 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 16 2025 |
| R-4.5-linux | OK | Mar 16 2025 |
| R-4.4-linux | OK | Mar 16 2025 |
Exports:seqICPseqICP.sseqICPnlseqICPnl.s
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Sequential Invariant Causal Prediction | seqICP-package seqICP_package |
| Sequential Invariant Causal Prediction | seqICP |
| Sequential Invariant Causal Prediction for an individual set S | seqICP.s |
| Non-linear Invariant Causal Prediction | seqICPnl |
| Non-linear Invariant Causal Prediction for an individual set S | seqICPnl.s |
| summary function | summary.seqICP |
| summary function | summary.seqICPnl |