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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