Packaged: 2016-09-26 18:16:28 UTC; mfernandes

Packaged: 2016-10-10 19:46:51 UTC; mfernandes

Author: Clayton Vieira Fraga Filho, Gilson Fernandes da Silva, Miqueias Fernandes
Imports: gsubfn, data.table, sqldf, plyr, randomcoloR, rbokeh, ggplot2

Imports: gsubfn, data.table, sqldf, plyr, randomcoloR, rbokeh
Packaged: 2017-07-18 17:32:56 UTC; mfernandes

Packaged: 2017-07-26 04:07:01 UTC; mfernandes

Title: Analysis of the International Trade Network
Description: Functions to clean and process international trade data into an international trade network (ITN) are provided. It then provides a set a functions to undertake analysis and plots of the ITN (extract the backbone, centrality, blockmodels, clustering). Examining the key players in the ITN and regional trade patterns.

Packaged: 2018-10-11 21:22:02 UTC; Matthew Smith

Title: Statistical Learning for Individualized Treatment Regime
Author: Chengchun Shi, Rui Song, Wenbin Lu and Bo Fu
Description: Maximin-projection learning (MPL, Shi, et al., 2018) is implemented for
recommending a meaningful and reliable individualized treatment regime for future
groups of patients based on the observed data from different populations with
heterogeneity in individualized decision making. Q-learning and A-learning are
implemented for estimating the groupwise contrast function that shares the same
marginal treatment effects. The packages contains classical Q-learning and A-learning
algorithms for a single stage study as a byproduct. More functions will be added

Title: Variable Selection for Optimal Individualized Dynamic Treatment
Author: Chengchun Shi, Ailin Fan, Rui Song and Wenbin Lu
Description: Sequential advantage selection (SAS, Fan, Lu and Song, 2016) <arXiv:1405.5239>
and penalized A-learning (PAL, Shi, et al., 2018) methods are implement for selecting
important variables involved in optimal individualized (dynamic) treatment regime in
both single-stage or multi-stage studies.
Imports: Formula, Rglpk, ncvreg, Matrix, svMisc

and penalized A-learning (PAL, Shi, et al., 2018) methods are implement for selecting important variables
involved in optimal individualized (dynamic) treatment regime in both single-stage or multi-stage studies.