Uses C++ via the 'Rcpp' package to parse modern Excel files ('.xlsx').
    Memory usage is kept minimal by decompressing only parts of the file at a time,
    while employing multiple threads to achieve significant runtime reduction.
    Uses <https://github.com/richgel999/miniz> and <https://github.com/lemire/fast_double_parser>.

Implements various methods for eliciting a probability
    distribution for a single parameter from an expert or a group of
    experts. The expert provides a small number of probability judgements,
    corresponding to points on his or her cumulative distribution
    function. A range of parametric distributions can then be fitted and
    displayed, with feedback provided in the form of fitted probabilities
    and percentiles. For multiple experts, a weighted linear pool can be
    calculated. Also includes functions for eliciting beliefs about
    population distributions; eliciting multivariate distributions using a
    Gaussian copula; eliciting a Dirichlet distribution; eliciting
    distributions for variance parameters in a random effects
    meta-analysis model; survival extrapolation. R Shiny apps for most of the methods are
    included.

Takes as input a stable oxygen isotope (d18O) profile measured in growth direction (D)
	through a shell + uncertainties in both variables (d18O_err & D_err). It then models the seasonality
	in the d18O record by fitting a combination of a growth and temperature sine wave to year-length chunks of
	the data (see Judd et al., (2018) <doi:10.1016/j.palaeo.2017.09.034>). This modeling is carried out along a sliding window through the data and yields estimates of
	the day of the year (Julian Day) and local growth rate for each data point. Uncertainties in both modeling
	routine and the data itself are propagated and pooled to obtain a confidence envelope around the age of
	each data point in the shell. The end result is a shell chronology consisting of estimated ages of shell
	formation relative to the annual cycle with their uncertainties. All formulae in the package serve this
	purpose, but the user can customize the model (e.g. number of days in a year and the mineralogy of the
	shell carbonate) through input parameters.