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nonlinearICP (version 0.1.2.1)

Invariant Causal Prediction for Nonlinear Models

Description

Performs 'nonlinear Invariant Causal Prediction' to estimate the causal parents of a given target variable from data collected in different experimental or environmental conditions, extending 'Invariant Causal Prediction' from Peters, Buehlmann and Meinshausen (2016), , to nonlinear settings. For more details, see C. Heinze-Deml, J. Peters and N. Meinshausen: 'Invariant Causal Prediction for Nonlinear Models', .

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install.packages('nonlinearICP')

Monthly Downloads

211

Version

0.1.2.1

License

GPL

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Maintainer

Christina Heinze-Deml

Last Published

July 31st, 2017

Functions in nonlinearICP (0.1.2.1)

summary.nonlinICP.class

summary function
varSelectionRF

Variable selection function that can be provided to nonlinearICP - it is then applied to pre-select a set of variables before running the ICP procedure on this subset. Here, the variable selection is based on random forest variable importance measures.
nonlinearICP

Nonlinear Invariant Causal Prediction
simData

Example dataset for tests