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GPCERF

Free plan Self-hosted

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What GPCERF is

GPCERF is a free, self-hosted package for estimating causal effects of a continuous exposure and identifying change points in causal exposure-response curves from observational data. Its nonparametric Bayesian framework uses Gaussian process priors, with standard Gaussian process and nearest-neighbor Gaussian process approaches. The documented workflow converts covariates into a composite generalized propensity score before fitting the model, then estimates an exposure-response function and plots a pointwise 95% credible band. Examples use CausalGPS for synthetic data generation and propensity-score estimation, ggplot2 for plotting, and the ranger R package at runtime. Installation uses R devtools and the GitHub develop branch. The nearest-neighbor example reports shorter running time than the standard workflow. The project is licensed under GPL (>= 3), with support through GitHub issues and Discussions. CRAN archived and removed it on 2026-01-12 because issues were not corrected despite reminders.

Who it suits

It suits users working with observational or simulated data who need Bayesian exposure-response estimation in R. Users should account for its self-hosted setup and archived CRAN status.

What it does well

  • Free plan with GPL (>= 3) license
  • Provides Gaussian process and nearest-neighbor methods
  • Produces pointwise 95% credible bands
  • Supports causal exposure-response workflows
  • Nearest-neighbor example reports shorter runtime

What to know first

  • Archived and removed from CRAN on 2026-01-12
  • Examples require the ranger R package
  • Installation uses the GitHub develop branch

Verdict

GPCERF provides documented Bayesian Gaussian-process workflows for causal exposure analysis. Its archived CRAN status and additional R dependencies are important considerations before adoption.

Facts from GPCERF's own pages

Bayesian analysis
Yes · nsaph-software.github.io, 23 Sept 2026
Bayesian framework
Its framework is nonparametric and Bayesian, based on Gaussian process priors. · nsaph-software.github.io, 12 Oct 2026
Covariate adjustment
The documented workflow converts covariate values into a composite generalized propensity score before fitting Gaussian processes. · nsaph-software.github.io, 12 Oct 2026
Covariate processing
The standard Gaussian process workflow converts covariate values into a composite score called the generalized propensity score before fitting Gaussian processes. · nsaph-software.github.io, 12 Oct 2026
Curve estimation
The standard Gaussian process workflow estimates an exposure-response function and visualizes a pointwise 95% credible band. · nsaph-software.github.io, 12 Oct 2026
Deployment
desktop · nsaph-software.github.io, 23 Sept 2026
Free plan
Yes · nsaph-software.github.io, 23 Sept 2026
Installation
The repository README shows installation from GitHub with devtools using the develop branch. · github.com, 12 Oct 2026
Integration
The documented examples use CausalGPS for synthetic data generation and GPS estimation, and ggplot2 for plotting. · nsaph-software.github.io, 12 Oct 2026
Intended users
The documented workflows estimate causal exposure-response functions from observational or simulated data. · nsaph-software.github.io, 12 Oct 2026
License
The project site lists the license as GPL (>= 3). · nsaph-software.github.io, 12 Oct 2026
Maintenance status
CRAN says GPCERF was removed on 2026-01-12 because issues were not corrected despite reminders. · cloud.r-project.org, 12 Oct 2026
Methods
The package provides Gaussian process and nearest-neighbor Gaussian process approaches for nonparametric modeling. · github.com, 12 Oct 2026
Outputs
The examples estimate exposure-response functions and plot pointwise 95% credible bands. · nsaph-software.github.io, 12 Oct 2026
Purpose
GPCERF estimates causal effects of a continuous exposure and detects change points in causal exposure-response curves using observational data. · nsaph-software.github.io, 12 Oct 2026
R dependencies
The repository installation example uses the R devtools package, and its usage note says examples also require the ranger R package. · github.com, 12 Oct 2026
Repository status
The CRAN page says GPCERF was archived on 2026-01-12 because issues were not corrected despite reminders. · cloud.r-project.org, 12 Oct 2026
Runtime dependency
The README notes that its usage examples also require the ranger R package. · github.com, 12 Oct 2026
Scaling option
The nearest-neighbor Gaussian process example reports much shorter running time than the standard Gaussian process example. · nsaph-software.github.io, 12 Oct 2026
Scripting support
Yes · nsaph-software.github.io, 23 Sept 2026
Support
The README directs users to report issues on GitHub and says they can seek assistance through GitHub Discussions or issues. · github.com, 12 Oct 2026

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