Hallin, M., Paindaveine, D. and Šiman, M. (2010)

Title: Modelling temperature effects using time series data
Description: Fits a Constrained Segmented Distributed Lag regression
model to epidemiological time series of mortality, temperature,

Description: Fits a Constrained Segmented Distributed Lag regression model
to epidemiological time series of mortality, temperature, and other confounders.

Title: Estimate ED50 Based on Modified Turning Point Method
Description: Turning point method is a method proposed by Choi (1990) <doi:10.2307/2531453> to
estimate 50 percent effective dose (ED50) in the study of drug sensitivity. The method has
its own advantages for that it can provide robust ED50 estimation. This package contains
the modified function of Choi's turning point method.

Title: A 'shiny' Module for Creating Charts of Various Types
Description: 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.
Imports: RColorBrewer, xts, dygraphs, highcharter, jsonlite, lazyeval,
networkD3, leaflet, lubridate, dplyr, reshape2, rgdal,
rpivotTable, shiny, shinyBS, shinyWidgets, shinydashboard,
shinydashboardPlus, sp, sunburstR, tidyr, treemap, DT,

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

Title: Fit a Modified Connor-Mosimann Distribution to Elicited
Authors@R: person("Ed", "Wilson", email = "ed.wilson@medschl.cam.ac.uk",
Description: 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.
Suggests: cowplot, ggplot2, tidyr, knitr, rmarkdown