crayon, dplyr, grantham, magrittr, purrr, rlang, seqinr,
stringr, tibble, tidyr, vctrs

crayon, dplyr, glue, grantham, magrittr, purrr, rlang, seqinr,
stringr, tibble, tidyr, vctrs

Methods for fitting additive hazards model.
Perform the maximum likelihood method as well as the traditional Aalen's method for estimating the additive hazards model.
For details see Chengyuan Lu(2021) <arXiv:2004.06156>.

Regularization for semiparametric additive hazards regression
Computationally efficient procedures for regularized
estimation with the semiparametric additive hazards regression
model.

Regularization for Semiparametric Additive Hazards Regression

An Implementation of the Artificial Hydrocarbon Networks
person("Jose Roberto", "Ayala Solares", email = "ichbinjras@gmail.com",
role = c("aut", "cre"))
Implementation of the Artificial Hydrocarbon Networks for data
modeling.
matrixcalc, pracma, purrr, pdist, ggplot2, visNetwork,
magrittr
Jose Roberto Ayala Solares <ichbinjras@gmail.com>

utils, data.tree, yaml, formattable, DiagrammeR
shiny, shinyAce, shinythemes, shinyjs, testthat, knitr,
rmarkdown
Model and analyse complex decision making problems
using the Analytic Hierarchy Process (AHP) by Thomas Saaty.

Analytic Hierarchy Process for Survey Data
person("Frankie", "Cho", email = "htcho@connect.hku.hk", role = c("aut", "cre"))
The Analytic Hierarchy Process is a versatile multi-criteria decision-making tool introduced by Saaty (1987) <doi:10.1016/0270-0255(87)90473-8> that allows decision-makers to weigh attributes and evaluate alternatives presented to them.    This package provides a consistent methodology for researchers to reformat data and run analytic hierarchy process in R on data that are formatted using the survey data entry mode. It is optimized for performing the analytic hierarchy process with many decision-makers, and provides tools and options for researchers to aggregate individual preferences and test multiple options. It also allows researchers to quantify, visualize and correct for inconsistency in the decision-maker's comparisons.
Rdpack, stats, magrittr, knitr, tidyr, dplyr
'ahp_mat.R' 'ahp_aggjudge.R' 'ahp_aggpref.R' 'ahp_bweight.R'
'ahp_cr.R' 'ahp_indpref.R' 'ahp_error.R' 'ahp_harker.R'
'ahp_missing.R' 'ahp_pwerror.R' 'ahpsurvey.R' 'data.R'