Package: VCMoE 0.1.0

Qicheng Zhao

VCMoE: Varying-Coefficient Mixture-of-Experts Models

Fits Gaussian, Binomial, and Negative-Binomial varying-coefficient mixture-of-experts models with local-linear estimation, explicit label alignment, bandwidth selection, diagnostics, bootstrap inference, analytic-style confidence bands, and coefficient-specific analytic GLRT diagnostics with optional bootstrap calibration.

Authors:Qicheng Zhao [aut, cre]

VCMoE_0.1.0.tar.gz
VCMoE_0.1.0.tar.gz(r-4.7-any)VCMoE_0.1.0.tar.gz(r-4.6-any)
VCMoE_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
VCMoE/json (API)

# Install 'VCMoE' in R:
install.packages('VCMoE', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/qc-zhao/vcmoe/issues

Pkgdown/docs site:https://qc-zhao.github.io

On CRAN:

Conda:

2.70 score 16 exports 17 dependencies

Last updated from:f94855fc9a. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK132
source / vignettesOK178
linux-release-x86_64OK121
wasm-releaseOK112

Exports:plot_coefficientsplot_diagnosticsplot_inferenceplot_posteriorsimulate_vcmoe_binomialsimulate_vcmoe_gaussiansimulate_vcmoe_negbinvcmoe_bootstrapvcmoe_confbandvcmoe_diagnosticsvcmoe_fitvcmoe_gating_contrastsvcmoe_glrtvcmoe_parameterizationvcmoe_scaled_slopesvcmoe_select_bandwidth

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

Gaussian VCMoE Simulation Tutorial

Rendered fromvcmoe-gaussian-no-offset.Rmdusingknitr::rmarkdownon Jun 19 2026.

Last update: 2026-06-19
Started: 2026-06-19