Title: Quantile Regression Forests for 'ranger'
Description: This is the implementation of quantile regression forests for the fast random forest package 'ranger'.

Title: Quantile-based Spectral Analysis of Time Series
Authors@R: c(person("Tobias","Kley", role = c("aut","cre"), email =
Depends: R (>= 2.12.0), quantreg, rje, tcltk, zoo
Description: Methods to determine, smooth and plot Laplace periodograms	and rank-based Laplace periodograms for univariate time series.

Depends: R (>= 2.14.0), quantreg, rje, tcltk, zoo

Imports: methods, graphics, quantreg, testthat, abind, zoo, rje,
Description: Methods to determine, smooth and plot quantile (i. e., Laplace or
copula) periodograms for univariate time series.
Packaged: 2014-04-27 13:58:54 UTC; tobias.kley

Packaged: 2014-06-05 20:42:13 UTC; tobias.kley

Imports: methods, graphics, quantreg, abind, zoo, snowfall, Rcpp (>=

Title: Quantile-Based Spectral Analysis of Time Series

person("Stefan", "Birr",  role = c("ctb"),
comment = "Contributions to lag window estimation", email = "stefan.birr@rub.de"))
Stefan Birr [ctb] (Contributions to lag window estimation)

Description: Methods to determine, smooth and plot quantile periodograms for
univariate and multivariate time series.

univariate and multivariate time series. See Kley (2016) <doi:10.18637/jss.v070.i03>

Title: Simple Methods for Calculating Value at Risk and Expected
comment = "Paderborn University, Germany")
Description: Enables the user to calculate Value at Risk (VaR)
and Expected Shortfall (ES) by means of various types of historical
simulation. Currently plain historical simulation as well as age- and
volatility-weighted historical simulation are implemented in this
package. Volatility weighting is carried out via an exponentially
weighted moving average (EWMA).  The methods of the package are
described in Gurrola-Perez, P. and Murphy, D. (2015)
Author: Sebastian Letmathe [aut, cre] (Paderborn University, Germany)

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 methods of the package are described in