The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

VCMoE

Varying-Coefficient Mixture-of-Experts Models

VCMoE is an R package for fitting varying-coefficient mixture-of-experts models. It supports Gaussian, Binomial, and Negative-Binomial responses, with local-linear estimation, component label alignment, bandwidth selection, diagnostics, confidence bands, bootstrap inference, and generalized likelihood-ratio tests.

The package is intended for problems where component-specific response relationships and component probabilities change along a continuous coordinate, such as time, pseudotime, dose, or spatial location.

Installation

Install the package from GitHub:

install.packages("remotes")
remotes::install_github("qc-zhao/VCMoE")

Load the package:

library(VCMoE)

Need help with installation or usage? Please open a GitHub issue:

https://github.com/qc-zhao/VCMoE/issues

Quick Start

set.seed(1)

sim <- simulate_vcmoe_gaussian(
  n = 300,
  k = 2,
  scenario = "well_separated"
)

fit <- vcmoe_fit(
  y ~ z1 | x1,
  data = sim$data,
  u = sim$data$u,
  k = 2,
  family = "gaussian",
  bandwidth = 0.25
)

coef(fit, "expert")
predict(fit, type = "posterior")
plot_coefficients(fit)

Documentation

The full documentation website includes a Gaussian simulation tutorial and function reference:

https://qc-zhao.github.io/VCMoE/

Useful links:

Citation

Please cite:

Zhao Q, Greenwood CMT, Zhang Q. Varying-Coefficient Mixture of Experts Model. arXiv:2601.01699. https://arxiv.org/abs/2601.01699

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.