Package: vbmp 1.81.0

Nicola Lama

vbmp: Variational Bayesian Multinomial Probit Regression

Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. It estimates class membership posterior probability employing variational and sparse approximation to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination.

Authors:Nicola Lama <[email protected]>, Mark Girolami <[email protected]>

vbmp_1.81.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
vbmp/json (API)

# Install 'vbmp' in R:

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

Datasets:

BRCA12 - BRCA tumour dataset

On BioConductor:vbmp-1.81.0(bioc 3.24)vbmp-1.80.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

classification

3.30 score 4 scripts 7 exports 0 dependencies

Last updated from:5a4fa80caf. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	170
linux-devel-x86_64	NOTE	115
source / vignettes	OK	153
linux-release-x86_64	NOTE	160
macos-release-arm64	NOTE	70
macos-oldrel-arm64	NOTE	80
windows-devel	NOTE	63
windows-release	NOTE	74
windows-oldrel	NOTE	71
wasm-release	OK	91

Exports:covParams plotDiagnostics predClass predError predictCPP predLik vbmp

Dependencies:

vbmp Tutorial

Rendered fromvbmp.Rnwusingutils::Sweave

Last update: 2013-11-01
Started: 2013-11-01

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
BRCA tumour dataset	BRCA12
VBMP covariance functions parameters	covParams
VBMP Lower bound estimate	lowerBound
VBMP covariance diagnostics plot	plotDiagnostics
VBMP Predicted class values	predClass
Out-of-Sample VBMP Prediction error	predError
VBMP predict functions parameters	predictCPP
VBMP predictive likelihood estimate	predLik
Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors.	vbmp