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

gsubfn, data.table, sqldf, plyr, randomcoloR, rbokeh

Analysis of the International Trade Network
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.

stats,circlize,GoodmanKruskal,graphics,RColorBrewer,
reshape2,maps,blockmodeling,igraph,utils,plyr,dplyr,
statnet,animation,Matrix,cowplot,ggplot2,GGally,
fastmatch,intergraph,sna,tnet,WDI,network,xergm,
xergm.common,networkDynamic,ndtv,comtradr

Statistical Learning for Individualized Treatment Regime
Chengchun Shi, Rui Song, Wenbin Lu and Bo Fu
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
at later versions.

Variable Selection for Optimal Individualized Dynamic Treatment
Regime
Chengchun Shi, Ailin Fan, Rui Song and Wenbin Lu
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.

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.