- Added option
`value`

to method`set`

in class`ModVar`

. This allows variables to be set to an explicit value; used in threshold finding. - Added
`threshold`

function to`DecisionTree`

to calculate the value of a model variable at which the cost difference becomes zero or ICER crosses a threshold. - Added option
`run`

to`by`

argument of`DecisionTree$evaluate()`

. Avoids application having to`reshape`

output before reporting PSA results. - Fixed bug in method
`DecisionTree$tornado`

which caused bars to be clipped under some circumstances. - Minor revisions to the Tegaderm vignette.

- Package tests that involve sampling randomly from a distribution and comparing the results with parameters of an expected distribution have been excluded when running CRAN tests. Otherwise the central limit theorem or empirical distributions are used to find 99.9% confidence limits on sample mean and SD.
- Added common test helpers and bespoke expectations to
`testthat/setup.R`

. - Changed vignette titles to reflect what kind of problem they illustrate, rather than the problems themselves, to make it clearer on the CRAN page.
- Added method
`as_DOT`

to`Graph`

and`Digraph`

for export to graphviz DOT file format to aid visualization of graphs.

- Added tests to give 100% coverage and replaced
`tolerance`

in`expect_equal`

with`abs`

in expect_true for approximate equality tests. - Further description for documentation.
- Converted vignettes to HTML.
- Added
`WORDLIST`

file and sundry administrative changes for clean package build. - Added
`README`

file, with an example and acknowledgements.

- Added
`draw()`

method to`DecisionTree`

. - Added
`tornado()`

method to`DecisionTree`

for univariate sensitivity analysis. - Optimized probabilistic sensitivity analysis loop in
`DecisionTree`

(1000 evaluations of a typical HTA tree takes < 5s on a typical PC).

- First full release of the package.
- Added graph theory classes. Decision trees and Markov models are forms of graph.
- Renamed
`ModelVariable`

as`ModVar`

for compactness, and renamed its derived classes similarly. - Added test harnesses for more classes.
- Collected vignette citations to file references.bib and changed to
*BMJ*csl style. - Added extra graph theory and decision tree vignettes.

- Removed the label argument from
`ModelVariable`

. - Improved auto-detection of variable label in
`ModelVariable`

. - Added NEWS.md and
`CITATION`

file to inst folder in CRAN preparation. - Added
`tests/testthat`

folder with tests for`ModelVariable`

. - Added scripts to call devtools::check/build on Windows/Mac.
- Fixed notes issued by R CMD check.

- Introduced the
`ModelVariable`

class as the new base class from which to construct the variables in an economic model. The class includes methods to support parametrization of uncertainty in the model variable. - Introduced sub-classes of
`ModelVariable`

to model particular forms of uncertainty. These are`ConstModelVariable`

,`NormalModelVariable`

,`GammaModelVariable`

,`BetaModelVariable`

,`LogNormalModelVariable`

. They do as expected from their names. Some support alternative forms of parametrization. - Introduced
`ExpressionModelVariable`

. A sub-class of`ModelVariable`

, objects of this class are defined with an expression involving other model variables. The concept permits variables to be combined in any mathematical expression that R itself will support. Because`ExpressionModelVariable`

s are themselves`ModelVariables`

, they can can appear in an expression that is used to define another model variable. - Introduced tabulation functions to list the properties of a model variable and its operands.
- Revised
`Node`

and its sub classes to accept`ModelVariables`

as arguments to costs, utilities and probabilities, thus embedding probabilistic sensitivity analysis into decision tree models. - Added the Tegaderm vignette. This is a published example of a decision tree model with PSA and is partial validation of the
`ModelVariable`

approach to PSA. - Updated the Sumatriptan vignette, after subsuming some of its pathway traversal code into
`Node`

classes. - Removed
`node.apply`

and`path.apply`

functions, and subsumed them into`Node`

. - Removed functions intended for use with
`node.apply`

and`path.apply`

, and subsumed them into`Node`

. - Provided
`Node`

objects with a Document Object Model (DOM) interface, as far as practicable.

- Moved citations in vignettes from external file
`references.bib`

to directly embed them in the YAML headers. To do: explore whether references can be saved in preferred bib format. - Replaced call to
`nullfile()`

, for suppressed output, in function`des`

with detection of OS to support older R versions (`nullfile`

was introduced to base R at 3.6.0).

- For the Markov solver:
- Function is now called
`des`

- It returns a list of summary matrices (the same ones written to csv files) instead of a single number.
- Output can be suppressed by setting stub=NA.
- Some minor bugs fixed.

- Function is now called

- First local release of rdecision as a package.
- Added classes for solving decision trees (
`Node`

,`LeafNode`

,`ChanceNode`

,`DecisionNode`

) and pathway detection and traversal functions. - Incorporated our discrete event solver, originally written in Matlab for the WatchBP model, then translated as a stand-alone R script, into the package.
- Added vignettes for Sumatriptan model from Briggs (Box 2.3) and from Sonnenberg and Beck’s original 3-state example.