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CausalMixGPD  

Bayesian Nonparametric Conditional Density Modeling in Causal Inference and Clustering with a Heavy-Tail Extension
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("CausalMixGPD", "0.8.0")



Attach the package and use:
library("CausalMixGPD")
Maintained by
Arnab Aich
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-21
Latest Update: 2026-04-21
Description:
The presence of a heavy tail is a feature of many scenarios when risk management involves extremely rare events. While parametric distributions may give adequate representation of the mode of data, they are likely to misrepresent heavy tails, and completely nonparametric approaches lack a rigorous mechanism for tail extrapolation; see Pickands (1975) <doi:10.1214/aos/1176343003>. The package 'CausalMixGPD' implements the semiparametric framework of Aich and Bhattacharya (2026) <doi:10.5281/zenodo.19620523> for Bayesian analysis of heavy-tailed outcomes by combining Dirichlet process mixture models for the body of the distribution with optional generalized Pareto tails. The method allows for unconditional and covariate-modulated mixtures, implements MCMC estimation using 'nimble', and extends to mixtures of different arms' outcomes with application to causal inference in the Rubin (1974) <doi:10.1037/h0037350> framework. Posterior summaries include density functions, quantiles, expected values, survival functions, and causal effects, with an emphasis on tail quantiles and functional measures sensitive to the tail.
How to cite:
Arnab Aich (2026). CausalMixGPD: Bayesian Nonparametric Conditional Density Modeling in Causal Inference and Clustering with a Heavy-Tail Extension. R package version 0.8.0, https://cran.r-project.org/web/packages/CausalMixGPD. Accessed 27 Oct. 2026.
Previous versions and publish date:
0.7.0 (2026-04-21 21:12), (2026-07-09 08:00)
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Complete documentation for CausalMixGPD
Functions, R codes and Examples using the CausalMixGPD R package
Full CausalMixGPD package functions and examples
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