Package: ivd 1.0.0.9000

Philippe Rast

ivd: "Individual Variance Detection"

Fit mixed-effects location scale models with spike-and-slab priors on the scale random effects to identify units with unusual residual variances. The method is described in detail in Carmo, Williams and Rast (2026) <doi:10.3102/10769986261426004>.

Authors:Philippe Rast [aut, cre, cph], Marwin Carmo [aut]

ivd_1.0.0.9000.tar.gz
ivd_1.0.0.9000.zip(r-4.7-any)ivd_1.0.0.9000.zip(r-4.6-any)ivd_1.0.0.9000.zip(r-4.5-any)
ivd_1.0.0.9000.tgz(r-4.6-any)ivd_1.0.0.9000.tgz(r-4.5-any)
ivd_1.0.0.9000.tar.gz(r-4.7-any)ivd_1.0.0.9000.tar.gz(r-4.6-any)
ivd_1.0.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ivd/json (API)

# Install 'ivd' in R:

install.packages('ivd', repos = c('https://consistentlybetter.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/consistentlybetter/ivd/issues

Datasets:

saeb - Basic Education Evaluation System (Saeb) -2021

On CRAN:

4.10 score 2 stars 21 scripts 202 downloads 8 exports 61 dependencies

Last updated from:48c10cb525. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	251
source / vignettes	OK	247
linux-release	OK	227
macos-release	OK	215
macos-oldrel	OK	210
windows-devel	OK	166
windows-release	OK	155
windows-oldrel	OK	147
wasm-release	OK	141

Exports:build_ivd_model codaplot fixef ivd pip pip_sensitivity ranef run_MCMC_compiled_model

Dependencies:abind backports BH callr checkmate cli coda codetools cpp11 desc digest distributional farver future generics ggplot2 ggrepel globals glue gridExtra gtable igraph inline isoband labeling lattice lifecycle listenv loo magrittr Matrix matrixStats nimble numDeriv otel parallelly patchwork pillar pkgbuild pkgconfig posterior pracma processx ps QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel rlang rstan S7 scales StanHeaders tensorA tibble utf8 vctrs viridisLite withr

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Helper to check for suggested package	.require_suggest
Build and compile NIMBLE model and MCMC once This function is exported for use in 'future' and is not meant to be called by user.	build_ivd_model
Traceplot from the coda package	codaplot
Extract coefficients from a fitted ivd model	coef.ivd
Extract fixed effects from a fitted ivd model	fixef fixef.ivd
Main function to set up and run parallel MCMC using nimble and future. 'ivd' computes a mixed effects location and scale model with Spike and Slab regularization on the scale random effects.	ivd
Extract PIPs from a fitted ivd model	pip pip.ivd
Analytic prior-sensitivity for PIPs	pip_sensitivity
Plot method for ivd objects	plot.ivd
Plot method for pip_sensitivity objects	plot.pip_sensitivity
Print method for ivd objects	print.ivd
Print method for summary.ivd objects	print.summary.ivd
Extract random effects from a fitted ivd model	ranef ranef.ivd
Run MCMC on an already compiled model Exposed but internal function for future()	run_MCMC_compiled_model
Basic Education Evaluation System (Saeb) -2021	saeb
Summary of posterior samples	summary.ivd