CODEWITHSUNDEEP
rcorrelationbayesian-networksbnlearn
mangoland
mangoland

Reputation: 13

Does bnlearn compute for non-linear correlations?

I've recently started using the bnlearn package in R for detecting Markov Blankets of a target node in the dataset.

Based on my understanding of Bayesian Inference, two nodes are connected if there is a causal relationship between the two and this is measured using some conditional independence tests to check for correlation while taking into account potential confounders.

I just wanted to clarify if bnlearn checks for both linear and non-linear correlations in these tests. I tried looking for stuff about this in the documentation for the package but I wasn't able to get anything.

It would be really helpful if someone can explain how bnlearn performs the CI tests.

Thanks a bunch <3

Upvotes: 1

Views: 244

Answers (1)

danlooo
danlooo

Reputation: 10627

Correlation implies statistical dependence, but not vice versa. There are cases of statistical dependence where there is no correlation, e.g. in periodic signals (correlation between sin(x) and x is very low for many periods). The concept of statistical dependence is more abstract than correlation and thus the documentation is written differently. As you can see in the example of sin(x) and x: This is indeed a non-linear dependency which should be captured by the Bayesian network.

Upvotes: 0

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