Description: Performs Principal Components Analysis (also known as PCA) dimensionality reduction in the context of a linear regression. In most cases, PCA dimensionality reduction is performed independent of the response variable for a regression. This captures the majority of the variance of the model's predictors, but may not actually be the optimal dimensionality reduction solution for a regression against the response variable. An alternative method, optimized for a regression against the response variable, is to use both PCA and a relative importance measure. This package applies PCA to a given data frame of predictors, and then calculates the relative importance of each PCA factor against the response variable. It outputs ordered factors that are optimized for model fit. By performing dimensionality reduction with this method, an individual can achieve a the same r-squared value as performing just PCA, but with fewer PCA factors. References: Yuri Balasanov (2017) <https://ilykei.com>.

Packaged: 2019-05-02 03:37:50 UTC; hernandez michael

Title: Renewal method for extreme values extrapolation
Author: Yves Deville <deville.yves@alpestat.com>, IRSN <renext@irsn.fr>
Suggests: MASS, graphics, ismev, evd, XML, numDeriv
Description: R package dedicated to some Extreme values problems and
allowing the use of the so-called "renewal method" which is

Depends: R (>= 2.8.0), stats, graphics, evd
Description: R package dedicated to some Extreme values problems and allowing the use of the so-called "methode du renouvellement" which is popular among french-speaking hydrologists.

Title: Renewal Method for Extreme Values Extrapolation
Description: Extreme value analysis using the Peaks Over Threshold (POT) method also called 'methode du renouvellement' by some French-speaking hydrologists.

Description: Peaks Over Threshold (POT) or 'methode du renouvellement'. The distribution for the exceedances can be chosen, and heterogeneous data (including historical data or block data) can be used in a Maximum-Likelihood framework.