Depends: R (>= 2.10.0), Lmoments, distillery, car
Description: Functions for performing extreme value analysis.

Depends: R (>= 2.10.0), Lmoments, distillery (>= 1.0-4)

Depends: R (>= 2.10.0), Lmoments, distillery (>= 1.0-4), car

Description: General functions for performing extreme value analysis.  In particular, allows for inclusion of covariates into the parameters of the extreme-value distributions, as well as estimation through MLE, L-moments, generalized (penalized) MLE (GMLE), as well as Bayes.  Inference methods include parametric normal approximation, profile-likelihood, Bayes, and bootstrapping.  Some bivariate functionality and dependence checking (e.g., auto-tail dependence function plot, extremal index estimation) is also included.  For a tutorial, see Gilleland and Katz (2016) <doi: 10.18637/jss.v072.i08> and for bootstrapping, please see Gilleland (2020) <doi: 10.1175/JTECH-D-20-0070.1>.

Title: Estimate the lower extreme quantile with the censored Weibull
Description: This package implements the subjectively censored Weibull MLE and censored Weibull mixture
for the lower quantile estimation. It also includes functions to evaluation the standard error of the resulting
quantile estimates. Also, the methods here can be used to fit the Weibull or Weibull mixture for
the Type-I or Type-II right censored data.

Title: Estimate Lower Extreme Quantile with the Censored Weibull MLE
Description: It implements the subjectively censored Weibull MLE and censored Weibull mixture methods for the lower quantile estimation. Quantile estimates from these two methods are robust to model misspecification in the lower tail. It also includes functions to evaluation the standard error of the resulting quantile estimates. Also, the methods here can be used to fit the Weibull or Weibull mixture for the Type-I or Type-II right censored data.

Title: Data Manipulation Extension Based on 'Dplyr' and 'Tidyr'
Authors@R: person("Yuchen", "Wang", email = "ycwang0712@gmail.com",
Description: If 'dplyr' is a grammar for data manipulation, 'extdplyr' is like
a short paragraph written in 'dplyr'. 'extdplyr' extends 'dplyr' and
'tidyr' verbs to some common "routines" that manipulate data sets. It uses
the same interface and preserves all the features from 'dplyr', has good
performance, and supports various data sources.