DESCRIPTION

Package: bremla
Type: Package
Title: Bayesian Regression Modeling of Layer-Counted Archives
Version: 0.1.0.9001
Authors@R: c(
    person("Eirik", "Myrvoll-Nilsen", email = "eirikmn91@gmail.com",
           role = c("aut","cre","cph"),
           comment = c(ORCID = "0000-0002-1643-5661"))
    )
Description: Performs efficient Bayesian regression modeling of layer-counted climate proxy records. This 
    model defines a probabilistic age-depth model using a generalized additive model (GAM), where physical 
    processes and systematic counting errors can be described using a regression model and the remaining 
    error can be explained using a noise process. The model is fitted to the accumulated number of layers 
    (number of counted layers per unit of depth) using integrated nested Laplace approximation via the 
    INLA package (<https://www.r-inla.org>). An ensemble of plausible chronologies are then sampled from 
    the estimated posterior distributions, on which further analyses can be performed such that dating 
    uncertainty propagation is treated rigorously. Additionally, the package also allows the chronologies 
    to be constrained using tie-points. The simulated chronologies can also be used to estimate the dating 
    uncertainty of the onsets of climate transitions. Details on the age-depth model in Myrvoll-Nilsen, 
    Riechers, Rypdal and Boers (2022) <doi:10.5194/cp-18-1275-2022>, and on how to incorporate tie-points 
    in Myrvoll-Nilsen, Riechers and Boers (preprint).
License: GPL (>= 2)
Imports: 
    numDeriv, 
    Matrix, 
    matrixStats, 
    ggplot2, 
    rlang, 
    stringr,
    utils
Depends: 
    R (>= 3.6),
    stats,
    methods
Additional_repositories: https://inla.r-inla-download.org/R/testing
Suggests: 
    INLA (>= 21.08.31),
    sn,
    sp (>= 1.4-5),
    rmarkdown,
    graphics,
    knitr
Encoding: UTF-8
LazyData: true
URL: https://github.com/eirikmn/bremla
BugReports: https://github.com/eirikmn/bremla/issues
RoxygenNote: 7.2.3
VignetteBuilder: knitr