Title: Functions for Extreme Value Distributions

Title: Bayesian Analysis in Extreme Value Theory
Description: Provides functions for the bayesian analysis of
extreme value models, using MCMC methods.
Packaged: Wed Jun  2 15:10:13 2004; stephena

Packaged: Mon Sep  6 17:42:10 2004; stephena

Packaged: Thu Mar  9 20:57:37 2006; stephena

Author: Alec Stephenson and Mathieu Ribatet.
Packaged: Tue Apr 18 13:18:05 2006; ribatema

Packaged: Wed Oct 18 16:24:50 2006; ribatema

Packaged: Sat Jul  5 19:51:46 2008; hornik

Description: Provides functions for the bayesian analysis of extreme

Description: Procedures for event history analysis

Title: Event History Procedures and Models
person("Bruce", "Swihart", email="bruce.swihart@gmail.com", role=c("cre", "aut")),
person("Jim"  , "Lindsey", email="jlindsey@gen.unimaas.nl", role="aut", comment="Jim created this package, Bruce is maintaining the CRAN version"))
Description: Functions for setting up and analyzing event history data.
Jim Lindsey [aut] (Jim created this package, Bruce is maintaining the

Packaged: 2018-05-24 17:48:50 UTC; swihartbj

Author: S original by J. Lee, K. Hess and J. Dubin.
R port by Laura Pontiggia <pontla@stat.umn.edu>.
Description: The function event.chart creates an event chart on the current

Author: S original by J. Lee, K. Hess and J. Dubin. R port by Laura Pontiggia <pontla@stat.umn.edu>

Title: Sequential event interval analysis
Description: Functions for analysis of rate changes in sequential events

Title: Sequential Event Interval Analysis

Description: Functions for analysis of rate changes in sequential events.

Title: Event Prediction for Time-to-Event Endpoints
Suggests: knitr, rmarkdown, rpact, fitdistrplus, gestate
Description: Implements the hybrid framework for event prediction described in Fang & Zheng (2011, <doi:10.1016/j.cct.2011.05.013>). To estimate the survival function the event prediction is based on, a piecewise exponential hazard function is fit to the time-to-event data to infer the potential change points. Prior to the last identified change point, the survival function is estimated using Kaplan-Meier, and the tail after the change point is fit using piecewise exponential.