A 'shiny' Module for Creating Charts of Various Types
This is a 'shiny' module that encapsulates various charting options available in 'htmlwidgets', and provides options for each type of chart, a 'crosstalk' like interface for aggregate reports between 'DT' and other chart types.
RColorBrewer, xts, dygraphs, highcharter, jsonlite, lazyeval,
networkD3, leaflet, lubridate, dplyr, reshape2, rgdal,
rpivotTable, shiny, shinyBS, shinyWidgets, shinydashboard,
shinydashboardPlus, sp, sunburstR, tidyr, treemap, DT,
sparkline, collapsibleTree, plotly

DT, RColorBrewer, collapsibleTree, dplyr, dygraphs,
highcharter, jsonlite, lazyeval, leaflet, networkD3, plotly,
rgdal, shiny, shinyBS, shinydashboard, shinydashboardPlus, sp,
sparkline, sunburstR, treemap, htmlwidgets, magrittr

Fit a Modified Connor-Mosimann Distribution to Elicited
Quantiles in Multinomial Problems
person("Ed", "Wilson", email = "ed.wilson@medschl.cam.ac.uk",
role = c("aut", "cre"))
Fits a modified version of the Connor-Mosimann distribution (Connor & Mosimann (1969)<doi:10.2307/2283728>),
a Connor-Mosimann distribution or Dirichlet distribution (e.g. Gelman, Carlin, Stern & Rubin Chapter 3.5 (2004, <ISBN:1-58488-388-X>) to elicited
quantiles of a multinomial distribution. Code is also provided to
sample from the distributions, generating inputs suitable for a
probabilistic sensitivity analysis / Monte Carlo simulation in a decision model.
cowplot, ggplot2, tidyr, knitr, rmarkdown

Compare Models with Cross-Validated Log-Likelihood
Shana Scogin <shanarscogin@gmail.com>, Sarah Petersen <sarahllpetersen@gmail.com>, Jeff Harden <jeff.harden@nd.edu>, Bruce A. Desmarais <bdesmarais@psu.edu>
An implementation of the cross-validated difference in means (CVDM) test by Desmarais and Harden (2014) <doi:10.1007/s11135-013-9884-7> (see also Harden and Desmarais, 2011 <doi:10.1177/1532440011408929>) and the cross-validated median fit (CVMF) test by Desmarais and Harden (2012) <doi:10.1093/pan/mpr042>. These tests use leave-one-out cross-validated log-likelihoods to assist in selecting among model estimations. You can also utilize data from Golder (2010) <doi:10.1177/0010414009341714> and Joshi & Mason (2008) <doi:10.1177/0022343308096155> that are included to facilitate examples from real-world analysis.
stats, quantreg, survival, coxrobust, methods, MASS, Rcpp