Title: Dynamic Network Communities Detection and Generation
Maintainer: Rui P. Sarmento <email@ruisarmento.com>
Description: Used for evolving network analysis regarding
community detection. Implements several algorithms that calculate communities
for graphs whose nodes and edges change over time.
Edges, which can have new nodes, can be added or deleted. Changes in the
communities are calculated without recalculating communities for the entire
Imports: Rcpp (>= 0.12.15), Rdpack, methods
Packaged: 2020-08-15 12:42:42 UTC; sarmentor
Author: Rui P. Sarmento [aut, cre] (<https://orcid.org/0000-0003-1891-5295>),

Title: Random Forest with Multivariate Longitudinal Predictors
person("Anthony", "Devaux", email = "anthony.devaux@u-bordeaux.fr",
Description: Based on random forest principle, 'DynForest' is able to include
multiple longitudinal predictors to provide individual predictions.
Longitudinal predictors are modeled through the random forest. The
methodology is fully described for a survival outcome in:
Devaux, Helmer, Dufouil, Genuer & Proust-Lima (2022)
Imports: DescTools, cmprsk, doParallel, foreach, ggplot2, lcmm,
methods, pbapply, pec, prodlim, stringr, survival, zoo
Author: Anthony Devaux [aut, cre] (<https://orcid.org/0000-0002-8862-4218>)

Title: A Dynamic Nomogram for Linear and Generalized Linear Models as
Author: Amirhossein Jalali, Alberto Alvarez-Iglesias, John Newell
Depends: ggplot2, stargazer, shiny, compare
Description: The DynNom function makes it possible to present the results of an
lm or glm model object as a dynamic nomogram that can be displayed in an R

Title: Dynamic Nomograms for Linear, Generalized Linear and
Author: Amirhossein Jalali, Alberto Alvarez-Iglesias, Davood Roshan Sangachin, John Newell
Description: Demonstrate the results of an lm(), glm() or coxph() model object as a dynamic nomogram that can be displayed in an 'RStudio' panel or web browser.
Imports: ggplot2, stargazer, shiny, compare, survival (>= 2.38-3)

Author: Amirhossein Jalali, Davood Roshan, Alberto Alvarez-Iglesias, John Newell
Description: Demonstrate the results of a statistical model object as a dynamic nomogram in an 'RStudio' panel or web browser. DynNom supports a variety of model objects; 'lm', 'glm', 'coxph' and also 'Ols', 'Glm', 'lrm', 'cph' models.
Depends: ggplot2, survival (>= 2.38-3), rms
Imports: shiny, stargazer, compare, BBmisc