Description: Performs the MRFA approach proposed by Sung et al. (2017+) <arXiv:1709.07064> to fit

Description: Performs the MRFA approach proposed by Sung et al. (2019+) <arXiv:1709.07064> to fit
Packaged: 2019-01-07 22:57:08 UTC; charliesung

Title: Markov Random Fields with Additional Covariates
person("Nicholas J", "Clark", email = "nicholas.j.clark1214@gmail.com", role = c("aut", "cre")),
person("Konstans", "Wells", email = "konswells@gmail.com", role = "aut"),
person("Oscar", "Lindberg", email = "o.lindberg@gmail.com", role = "aut"))
Maintainer: Nicholas J Clark <nicholas.j.clark1214@gmail.com>
Description: Approximate node interaction parameters of Markov Random Fields
graphical networks. Models can incorporate additional covariates, allowing users to estimate
how interactions between nodes in the graph are predicted to change across
covariate gradients. The general methods implemented in this package are described
Imports: purrr, parallel, plyr, ggplot2, dplyr, caret, gridExtra,
magrittr, Matrix, stats, utils, reshape2, sfsmisc, igraph,
Packaged: 2018-08-20 23:03:32 UTC; nicholasclark

Packaged: 2018-11-26 06:18:01 UTC; nicholasclark

Packaged: 2019-04-10 05:53:24 UTC; nicholasclark

Packaged: 2021-03-18 06:05:39 UTC; nicholasclark

Title: Multi-Resolution Estimation of the Hazard Rate
Author: Yolanda Hagar, Yuanting Chen, Vanja Dukic
Description: Used on survival data to jointly estimate the hazard rate and the effects of covariates on failure times.

Description: Used on survival data to jointly estimate the hazard rate and the effects of covariates on failure times. Can accommodate covariates under the proportional and non-proportional hazards setting, and is ideal for analysis of survival data with long-term follow-up.

Title: Multivariate Renewal Hawkes Process
Description: Simulate a (bivariate) multivariate renewal Hawkes (MRHawkes)
self-exciting process, with given immigrant hazard rate functions and
offspring density function. Calculate the likelihood of a MRHawkes process
with given hazard rate functions and offspring density function for an
(increasing) sequence of event times. Calculate the Rosenblatt residuals of the
event times. Predict future event times based on observed event times up to a
given time. For details see Stindl and Chen (2018) <doi:10.1016/j.csda.2018.01.021>.
Packaged: 2018-08-20 01:02:54 UTC; tomstindl