Sequential Monte Carlo (SMC) algorithms for fitting a generalised additive mixed model (GAMM) to surface-enhanced resonance Raman spectroscopy (SERRS), using the method of Moores et al. (2016) <doi:10.48550/arXiv.1604.07299>. Multivariate observations of SERRS are highly collinear and lend themselves to a reduced-rank representation. The GAMM separates the SERRS signal into three components: a sequence of Lorentzian, Gaussian, or pseudo-Voigt peaks; a smoothly-varying baseline; and additive white noise. The parameters of each component of the model are estimated iteratively using SMC. The posterior distributions of the parameters given the observed spectra are represented as a population of weighted particles.
| Version: | 0.5-0 |
| Depends: | R (≥ 3.5.0), Matrix, truncnorm, splines |
| Imports: | Rcpp (≥ 0.11.3), methods |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | testthat, knitr, rmarkdown, Hmisc |
| Published: | 2021-06-28 |
| DOI: | 10.32614/CRAN.package.serrsBayes |
| Author: | Matt Moores |
| Maintainer: | Matt Moores <mmoores at gmail.com> |
| BugReports: | https://github.com/mooresm/serrsBayes/issues |
| License: | GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE] |
| URL: | https://github.com/mooresm/serrsBayes, https://mooresm.github.io/serrsBayes/ |
| NeedsCompilation: | yes |
| Citation: | serrsBayes citation info |
| Materials: | README, NEWS |
| In views: | ChemPhys |
| CRAN checks: | serrsBayes results |
| Reference manual: | serrsBayes.html , serrsBayes.pdf |
| Vignettes: |
Introducing serrsBayes (source, R code) Methanol example (source, R code) |
| Package source: | serrsBayes_0.5-0.tar.gz |
| Windows binaries: | r-devel: serrsBayes_0.5-0.zip, r-release: serrsBayes_0.5-0.zip, r-oldrel: serrsBayes_0.5-0.zip |
| macOS binaries: | r-release (arm64): serrsBayes_0.5-0.tgz, r-oldrel (arm64): serrsBayes_0.5-0.tgz, r-release (x86_64): serrsBayes_0.5-0.tgz, r-oldrel (x86_64): serrsBayes_0.5-0.tgz |
| Old sources: | serrsBayes archive |
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