Depends: R (>= 3.0.0), matrixcalc, xtable

Title: Statistical Significance of the Sharpe Ratio
Description: A collection of tools for analyzing significance of trading
Suggests: xtable, xts, quantmod, MASS, TTR, testthat, sandwich, knitr
Collate: 'SharpeR.r' 'utils.r' 'distributions.r' 'sr.r' 'estimation.r'

Suggests: xtable, xts, timeSeries, quantmod, MASS, TTR, testthat,

Description: A collection of tools for analyzing significance of assets,
funds, and trading strategies, based on the Sharpe ratio and overfit
of the same. Provides density, distribution, quantile and random generation
of the Sharpe ratio distribution based on normal returns, as well
as the optimal Sharpe ratio over multiple assets. Computes confidence intervals
on the Sharpe and provides a test of equality of Sharpe ratios based on
Imports: matrixcalc, methods, sadists (>= 0.2.0)

the Delta method. The statistical foundations of the Sharpe can be found in
the author's Short Sharpe Course  <doi:10.2139/ssrn.3036276>.
Collate: 'SharpeR.r' 'data.r' 'utils.r' 'distributions.r' 'sr.r'

person("Felix", "Henze", email="felixhenze0@gmail.com", role=c("aut", "cre")),
person("Rich", "Geldreich", role=c("ctb", "cph"), comment="Author of included miniz code"),
person("Eric", "Biggers", role=c("ctb", "cph"), comment="Author of included libdeflate code"),
person("Daniel", "Lemire", role=c("ctb", "cph"), comment="Author of included fast_double_parser code")
Description: 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.
Rich Geldreich [ctb, cph] (Author of included miniz code),
Eric Biggers [ctb, cph] (Author of included libdeflate code),
Daniel Lemire [ctb, cph] (Author of included fast_double_parser code)

Title: Builds Chronologies from Oxygen Isotope Profiles in Shells
Description: 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 modelling 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 modelling
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.
Packaged: 2020-11-18 12:41:45 UTC; Convernaum
Author: Niels de Winter [aut, cre] (<https://orcid.org/0000-0002-1453-5407>)
Maintainer: Niels de Winter <niels_de_winter@live.nl>