Package: serrsBayes
Type: Package
Title: Bayesian Modelling of Raman Spectroscopy
Version: 0.6-1
Date: 2026-10-05
Authors@R: c(
    person("Matt", "Moores", role = c("aut", "cre"), email = "mmoores@gmail.com", comment = c(ORCID = "0000-0003-4531-3572")),
    person("Jake", "Carson", role="aut", email="Jake.Carson@warwick.ac.uk", comment = c(ORCID = "0000-0002-7896-0971")),
    person("Dirk", "Eddelbuettel", role = "ctb", comment = c(ORCID = "0000-0001-6419-907X")),
    person("Benjamin", "Moskowitz", role="ctb", comment = c(ORCID = "0000-0003-1005-8639")),
    person("Kirsten", "Gracie", role="dtc"),
    person("Karen", "Faulds", role="dtc", comment = c(ORCID = "0000-0002-5567-7399")),
    person("Duncan", "Graham", role="dtc", comment = c(ORCID = "0000-0002-6079-2105")),
    person("Mark", "Girolami", role="aut", comment = c(ORCID = "0000-0003-3008-253X")),
    person("Engineering and Physical Sciences Research Council", role="fnd", comment="EPSRC programme grant ref: EP/L014165/1"),
    person("University of Warwick", role="cph"))
Description: 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. (2026) <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.
License: GPL (>= 2) | file LICENSE
URL: https://github.com/mooresm/serrsBayes,
        https://mooresm.github.io/serrsBayes/
BugReports: https://github.com/mooresm/serrsBayes/issues
Depends: R (>= 3.5.0), Matrix, truncnorm, splines
Imports: Rcpp (>= 0.11.3), methods
LinkingTo: Rcpp, RcppEigen
Suggests: testthat, knitr, rmarkdown, Hmisc
LazyData: true
Encoding: UTF-8
VignetteBuilder: knitr
Config/roxygen2/version: 8.1.0
Repository: https://mooresm.r-universe.dev
Date/Publication: 2026-10-19 06:00:06 UTC
RemoteUrl: https://github.com/mooresm/serrsbayes
RemoteRef: HEAD
RemoteSha: bfbb8164308daa75d6e86218d4dde2a0a0fc2975
NeedsCompilation: yes
Packaged: 2026-10-19 06:53:25 UTC; root
Author: Matt Moores [aut, cre] (ORCID: <https://orcid.org/0000-0003-4531-3572>),
  Jake Carson [aut] (ORCID: <https://orcid.org/0000-0002-7896-0971>),
  Dirk Eddelbuettel [ctb] (ORCID:
    <https://orcid.org/0000-0001-6419-907X>),
  Benjamin Moskowitz [ctb] (ORCID:
    <https://orcid.org/0000-0003-1005-8639>),
  Kirsten Gracie [dtc],
  Karen Faulds [dtc] (ORCID: <https://orcid.org/0000-0002-5567-7399>),
  Duncan Graham [dtc] (ORCID: <https://orcid.org/0000-0002-6079-2105>),
  Mark Girolami [aut] (ORCID: <https://orcid.org/0000-0003-3008-253X>),
  Engineering and Physical Sciences Research Council [fnd] (EPSRC
    programme grant ref: EP/L014165/1),
  University of Warwick [cph]
Maintainer: Matt Moores <mmoores@gmail.com>