Package: BBEST 0.1-8

BBEST: Bayesian Estimation of Incoherent Neutron Scattering Backgrounds

We implemented a Bayesian-statistics approach for subtraction of incoherent scattering from neutron total-scattering data. In this approach, the estimated background signal associated with incoherent scattering maximizes the posterior probability, which combines the likelihood of this signal in reciprocal and real spaces with the prior that favors smooth lines. The description of the corresponding approach could be found at Gagin and Levin (2014) <doi:10.1107/S1600576714023796>.

Authors:Anton Gagin and Igor Levin with contributions from Charles R. Hogg III

BBEST_0.1-8.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
BBEST/json (API)
NEWS

# Install 'BBEST' in R:

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

On CRAN:

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

2.00 score 4 scripts 270 downloads 2 mentions 75 exports 49 dependencies

Last updated from:0298a3cac0. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	146
source / vignettes	OK	186
linux-release-x86_64	NOTE	138
macos-release-arm64	NOTE	158
macos-oldrel-arm64	NOTE	159
windows-devel	NOTE	97
windows-release	NOTE	86
windows-oldrel	NOTE	85
wasm-release	OK	113

Exports:basisMatrix basisSpline bkg.analyt calc.Gr covMatrix.DI covMatrixSE DMatrix do.fit do.fit.banks do.iter Dx fix.merge fplot.Gr get.bkg get.deriv get.hess get.hess.numerically get.posterior golden.search grad.descent guide invert.order logLikelihoodBkg logLikelihoodBkgAnalyt logLikelihoodGrCorr logLikelihoodGrGauss logLikelihoodSignal logLikelihoodSignalAnalyt logPosterior logPosteriorAnalyt logPriorBkgRGP logPriorBkgRSmooth logPriorF logProbabilityBkgR mPlot.results mPlot.results.banks mPlot.sqa noise.cov.matrix.r noise.cov.r noise.cov.vector.r prepare.banks.data Progress progressInit read.data read.sqa read.sqb regularized.cholesky row.outer.product runUI set.control set.data set.DEoptim.control set.Gr set.lambda set.SB set.sigma setProgress sineFT sineFT.matrix sqa.split step1 step10 step2 step3 step5 step6 step7 step8 step9 test.signal trim.data whatIsSpecified withProgress write.fit.results write.fix

Dependencies:aws awsMethods base64enc bslib cachem cli commonmark cpp11 DEoptim digest farver fastmap fontawesome fs ggplot2 glue gsl gtable htmltools httpuv isoband jquerylib jsonlite labeling later lifecycle magrittr memoise mime otel plyr promises R6 rappdirs RColorBrewer Rcpp reshape2 rlang S7 sass scales shiny sourcetools stringi stringr vctrs viridisLite withr xtable

Help page	Topics
Bayesian Background Estimation.	BBEST-package BBEST
Calculate and plot the Pair Distribution Function	calc.Gr
Estimate background	do.fit
Estimate the background for individual banks	do.fit.banks
Estimate the background	do.iter
Merge .fix files	fix.merge
BBEST guide	guide
Plot the background estimate	mPlot.results
Plot the background estimate for individual banks	mPlot.results.banks
Plot the total normalized scattering intensity function 'S(Q)' for individual detector banks	mPlot.sqa
Prepare data for estimating the background	prepare.banks.data
Reporting progress (object-oriented API)	Progress Progress-class
Initialize progress	progressInit
Read data from file	read.data
Read data from a '.sqa'-file	read.sqa
Read data from a '.sqb'-file	read.sqb
Start the GUI	runUI
Set controls for the Differential Evolution Algorithm	set.control
Set data	set.data
Add information on the low-r behaviour of G(r)	set.Gr
Set mean signal magnitude	set.lambda
Set the coherent baseline	set.SB
Set the experimental uncertainty	set.sigma
Split .sqa file into individual files for each databank	sqa.split
A random function with a smooth background	test.signal
Truncate data	trim.data
Reporting progress (functional API)	setProgress withProgress
Save results of the fit	write.fit.results
Save a correction file for individual detector banks	write.fix

Package: BBEST 0.1-8

BBEST: Bayesian Estimation of Incoherent Neutron Scattering Backgrounds

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