Simple Methods for Calculating and Backtesting Value at Risk and
Expected Shortfall
Enables the user to calculate Value at Risk (VaR)
and Expected Shortfall (ES) by means of various types of historical
simulation. Currently plain-, age-, volatility-weighted- and filtered
historical simulation are implemented in this package. Volatility weighting
can be carried out via an exponentially weighted moving average model
(EWMA) or other GARCH-type models. The performance can be assessed via
Traffic Light Test, Coverage Tests and Loss Functions. The methods of the
package are described in Gurrola-Perez, P. and Murphy, D. (2015)
<https://EconPapers.repec.org/RePEc:boe:boeewp:0525> as well as McNeil, J.,
Frey, R., and Embrechts, P. (2015) <https://ideas.repec.org/b/pup/pbooks/10496.html>.
graphics, progress, rugarch, smoots, stats

dygraphs, ggplot2, graphics, progress, rugarch, shiny,
shinyjs, smoots, stats, yfR, xts

Interaction Prediction Between Groundwater and Quarry Extension
Using Discrete Choice Models and Artificial Neural Networks
c(
person("Johan", "Barthelemy", role = c("aut", "cre"),
email = "johan@uow.edu.au"),
person("Timoteo", "Carletti", role = "aut"),
person("Louise", "Collier", role = "aut"),
person("Vincent", "Hallet", role = "aut"),
person("Marie", "Moriame", role = "aut"),
person("Annick", "Sartenaer", role = "aut"))
Johan Barthelemy [aut, cre], Timoteo Carletti [aut],
Louise Collier [aut], Vincent Hallet [aut], Marie Moriame [aut],
Annick Sartenaer [aut]
An implementation of two interaction indices between extractive
activity and groundwater resources based on hazard and vulnerability
parameters used in the assessment of natural hazards. One index is based
on a discrete choice model and the other is relying on an artificial
neural network.

R Interface to 'Quarto' Markdown Publishing System
person(given = "JJ",
family = "Allaire",
role = c("aut", "cre"),
email = "jj@rstudio.com",
comment = c(ORCID = "0000-0003-0174-9868"))
Convert R Markdown documents and 'Jupyter' notebooks to a variety of
output formats using 'Quarto'.
Quarto command line tools
(https://github.com/quarto-dev/quarto-cli).