Other packages > Find by keyword >

seqICP  

Sequential Invariant Causal Prediction
View on CRAN: Click here


Download and install seqICP package within the R console
Install from CRAN:
install.packages("seqICP")

Install from Github:
library("remotes")
install_github("cran/seqICP")

Install by package version:
library("remotes")
install_version("seqICP", "1.1")



Attach the package and use:
library("seqICP")
Maintained by
Niklas Pfister
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-06-27
Latest Update: 2017-07-25
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.
How to cite:
Niklas Pfister (2017). seqICP: Sequential Invariant Causal Prediction. R package version 1.1, https://cran.r-project.org/web/packages/seqICP. Accessed 07 Jun. 2026.
Previous versions and publish date:
1.0 (2017-06-27 08:40), 1.1 (2017-07-25 16:54)
Other packages that cited seqICP R package
View seqICP citation profile
Other R packages that seqICP depends, imports, suggests or enhances
Complete documentation for seqICP
Functions, R codes and Examples using the seqICP R package
Some associated functions: seqICP . seqICP.s . seqICP_package . seqICPnl . seqICPnl.s . summary.seqICP . summary.seqICPnl . 
Some associated R codes: seqICP.R . seqICP.s.R . seqICPnl.R . seqICPnl.s.R . summary.seqICP.R . summary.seqICPnl.R .  Full seqICP package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

curtailment  
Finds Binary Outcome Designs Using Stochastic Curtailment
Finds single- and two-arm designs using stochastic curtailment, as described by Law et al. (2022) ...
Download / Learn more Package Citations See dependency  
roxygen2  
In-Line Documentation for R
Generate your Rd documentation, 'NAMESPACE' file, and collation field using specially formatted com ...
Download / Learn more Package Citations See dependency  
cesR  
Access the Canadian Election Study Datasets
Makes accessing and loading the Canadian Election Study (, ...
Download / Learn more Package Citations See dependency  
xmlr  
Read, Write and Work with 'XML' Data
'XML' package for creating and reading and manipulating 'XML', with an object model based on 'Refere ...
Download / Learn more Package Citations See dependency  
gRain  
Bayesian Networks
Probability propagation in graphical independence networks, also known as Bayesian networks or prob ...
Download / Learn more Package Citations See dependency  
r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  

27,372

R Packages

233,548

Dependencies

72,820

Author Associations

27,205

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA