Authors@R: c(person("Courtney", "Paulson", email = "courtneypaulson@suu.edu", role = c("aut", "cre")),person("Lan", "Luo", role="ctb"),person("Gareth","James",role="ctb"))
for journal text/citation and <http://faculty.marshall.usc.edu/gareth-james/Research/ELMSO.pdf>
Packaged: 2020-01-17 21:29:35 UTC; courtneypaulson

Title: Extreme Learning Machine for Survival Analysis
Description: We use the Buckley-James method to impute the data and extend the emerging Extreme Learning Machine approach to survival analysis. Currently, only right censored data are supported. For a detailed information, see the paper by Hong Wang, Jianxin Wang and Lifeng Zhou (2017) <https://github.com/whcsu/ELMSurv/blob/master/elmsurv-revised.pdf>, which will appear in Applied Intelligence <https://link.springer.com/journal/10489> soon.

Description: First, we use the Buckley-James method to impute the data and extend the emerging extreme learning machine approach to survival analysis. Second, we present a kernel extreme learning machine Cox model regularized by an L_0-based broken adaptive ridge (BAR) penalization method. For a detailed information, see Hong Wang et al(2018) <DOI: 10.1007/s10489-017-1063-4>, Hong Wang and Gang Li(2019) <DOI:10.1002/sim.8090>.

Title: ELT - A package to build Experience Life Tables
Author: Julien Tomas, Frederic Planchet, Wassim Youssef
Description: The package is meant to help actuaries to build experience life tables. It contains functions to calculate exposure and number of deaths, smoothing following four different methods, and validation following three criteria.
Depends: R (>= 2.10.0), locfit, lattice, latticeExtra, grid, xlsx

Description: Build experience life tables.
Depends: R (>= 2.10.0), locfit, lattice, latticeExtra, xlsx

Description: Empirical likelihood ratio tests for the Yang and Prentice (short/long term hazard ratio) models.
Empirical likelihood tests within a Cox model, for parameters defined via
both baseline hazard function and regression parameters.
Title: Empirical Likelihood Analysis for the Cox Model and