Packaged: 2019-12-09 11:49:35 UTC; Wagner Jorge

Packaged: 2020-05-24 16:07:45 UTC; Wagner Jorge

Title: Use Time Series to Generate and Compare Power Spectral Density
Description: Functions that allow you to generate and compare power spectral density (PSD)
plots given time series data. Fast Fourier Transform (FFT) is used to take a time series
data, analyze the oscillations, and then output the frequencies of these oscillations
in the time series in the form of a PSD plot.Thus given a time series, the dominant
frequencies in the time series can be identified. Additional functions in this package
allow the dominant frequencies of multiple groups of time series to be compared with each other.
To see example usage with the main functions of this package, please visit
The mathematical operations used to generate the PSDs are described in these sites:
Imports: devtools (>= 2.4.1), ggplot2 (>= 3.3.2), qpdf (>= 1.1), stats
Maintainer: Yong-Han Hank Cheng <yhhc@uw.edu>

Title: Parameter space exploration with Latin Hypercubes
Author: Andre Chalom, Paulo Inacio Knegt Lopez de Prado
Depends: R (>= 3.0.1), sensitivity, Hmisc, boot
Description: Functions for creating Latin Hypercubes with
prescribed correlations and performing parameter space exploration.

Based on the package sensitivity, by Gilles Pujol,

Depends: R (>= 3.0.1), Hmisc, boot, parallel

Title: Parameter Space Exploration with Latin Hypercubes
Imports: utils, graphics, stats, boot, parallel

Description: Various functions for computing pseudo-observations for
Packaged: Wed Oct 10 08:32:43 2007; Maja

Author: Maja Pohar Perme [aut], Mette Gerster [aut, cre]

Title: Computes Pseudo-Observations for Modeling
Description: Various functions for computing pseudo-observations for censored data regression. Computes pseudo-observations for modeling: competing risks based on the cumulative incidence function, survival function based on the restricted mean,  survival function based on the Kaplan-Meier estimator see Klein et al. (2008) <doi:10.1016/j.cmpb.2007.11.017>.
Author: Maja Pohar Perme [aut], Mette Gerster [aut], Kevin Rodrigues [cre]