Title: Utility Functions for Parametric Multi-State Models
Description: Provides functions for working with multi-state modelling,
such as efficient simulation routines for estimating transition probabilities and length of stay.
It is designed as an extension to multi-state modelling capabilities provided with the 'flexsurv'
Imports: Rcpp (>= 0.12.10), data.table, dplyr, magrittr, networkD3,
Suggests: flexsurv, mstate, microbenchmark, rmarkdown, knitr

Suggests: flexsurv, mstate, microbenchmark, rmarkdown, knitr, testthat,

Imports: data.table, dplyr, magrittr, networkD3, tidyr, webshot
Suggests: covr, knitr, flexsurv, mstate, microbenchmark, rmarkdown,

Imports: data.table, dplyr, magrittr, networkD3, tidyr

Package: multitable
Type: Package
Title: Simultaneous manipulation of multiple arrays of data, with
data.list objects
Version: 1.0
Date: 2011-07-17
Author: Steve C Walker
Maintainer: Steve C Walker <steve.walker@utoronto.ca>
Description: Data frames are integral to R.  They provide a standard
format for passing data to model-fitting and plotting
functions.  This standard makes it easier for experienced useRs
to learn new functions, because most developments in R continue
to accept a single data frame as input.  Still, many data sets
do not easily fit into a single data frame, and my field of
community ecology provides many examples of such inherently
multiple-table data (e.g. fourth-corner problem and other
trait-based data sets).  Storing such data in a single data
frame results in either large numbers of meaningless missing
values or storage of redundant information.  These storage
problems have led ecologists to model summaries of their data
(e.g. community-weighted trait matrices), rather then their
data itself.  Perhaps more importantly, my experience with
manipulating such data using data frames has resulted in
difficult-to-read workflows with many lines.  The multitable
package introduces new data storage objects called data.lists,
which are extensions of data.frames.  As data.lists can be
coerced to data.frames, they can be used with all R functions
that accept an object that is coercible to a data.frame (e.g.
lm; plot; lme; and many more).  The multitable package also
provides several mechanisms for simplifying the manipulation of
data.list objects.
Suggests: MASS, lattice
License: GPL-2
LazyLoad: yes
Packaged: 2011-09-29 12:27:52 UTC; stevenwalker
Repository: CRAN
Date/Publication: 2011-09-29 15:19:11