Causal inference is a branch of scientific inquiry that seeks to understand the relationship between cause and effect. It involves studying the factors that lead to a particular outcome or event and identifying the causal relationships between them. Causal research is often used in fields such as medicine, psychology, and social sciences to identify the causes of various phenomena and to develop interventions that can effectively address them.
Questions tagged [causality]
136 questions
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Finding if X and Y are independent given a list of variables Z = [Z1,...,Zn]
I am running the pc-algorithm for causal networks. In this algorithm, I need to verify if two arrays X and Y are independent given a set of arrays Z1,..., Zn. In papers, it is usually assumed gaussian independence tests, which I am trying not to use…
donut
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Improving prediction accuracy in Bayesian Causal Network
I would like to determine the causes of an unexpected outcome (or anamoly) in a thermodynamic process. I have continuous data of the associated variables and trying to make use of 'Bayesian Network (BN)' for the determination of causality…
ajay1720
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Error in 'indepTest' in PC algorithm for conditional Independence Test
I am using PC algorithm function, in which Conditional Independence is one of the attribute. Facing error in the following code. Note that 'data' here is the data that I have been using, and 1,6,2 in gaussCItest are the node positions in my…
Divya Athyala
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Toda-Yamamoto Granger Causality Test in Python
I am trying to perform the Toda - Yamamoto procedure of Granger Causality testing with Python statsmodels between two series: stock price and interest rate. The procedure is clearly explained here:…
Van Vi
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Interpreting the confidence interval from CausalImpact
I am not sure how to interpret the confidence interval obtained when using the CausalImpact function in the CausalImpact R package.
I am confused because I think there is a contradiction - the model is returning a very low p-value (0.009) which…
Tom Roth
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Multivariate Granger's causality
I'm having issues doing a multivariate Granger's causal test. I'll like to check if conditioning a third variable affects the results of a causal test.
Here's one sample for a single dependent and independent variable based on an earlier question I…
Joke O.
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Errors using CausalImpact package with Zoo objects
I'm trying to model the impact of storms on sales patterns using the CausalImpact package. When I create a zoo object and pass it to the model I receive an error. I've read through the documentation and can't figure out what I'm doing differently…
Matt Phair
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R bnlearn package: prevent node from having any parents
Using the package bnlearn, is it possible to set a node to not be able to have any parents? I've found it is technically possible using the blacklist function. Example preventing "A" from having any parents in the included test…
splicer
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Replicating the Example of Error Correction Model (ECM) in R?
I have used EViews and run Error Correction Model (ECM) and obtained some result. Now I would like to replicate that example in R and obtain the same result like I did in EViews.
The data I have used are as follows:
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Robin Hood
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How to run Error Correction Model in R?
Used functions, packages and data:
I used 2 time series, having 51 observation…
Robin Hood
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Granger causality test using VECM in R
I am trying to compute the Granger causality test using the Vector Error Correction Model (VECM) in R. I calculated the VECM in R using tsDyn package. Since I have I(1) and cointegrated variables, VECM is assumed to implement the Granger causality…
vgordi
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How to find parameters for Granger causality(VAR)?
Does anyone know how to find parameters in Granger causality (vector autoregression model)?
I've found how to estimate them, but how do people usually set these parameters up?
user3532007
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Can the pre and post intervention periods be reversed in order in CausalImpact in R?
In CausalImpact library in R, usually the pre period is considered as the period where the campaign was inactive and the post period is considered as the period after the intervention of the campaign. So the data for pre-period is considered as 0…
T_S
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Is there a causal relation between two endogeneous variables from a structural model?
Suppose there are two variables both of which are endogeneized in a structural model. For instance, people's retirement decision ($X_1$) and saving behavior ($X_2$) are endogeneous because they are the results of the utility optimization procedure…
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How to test for Granger Causality in Python (Toda & Yamamoto style)?
I am trying to implement the process for Granger Causality testing outlined in this blogpost by Dave Giles, which I understand is a famous post about performing a Granger Causality test for non-stationary data, following the Toda-Yamamoto method. He…
chaserone10
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