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Description

The R Interface to 'SyncroSim'.

'SyncroSim' is a generalized framework for managing scenario-based datasets (<https://syncrosim.com/>). 'rsyncrosim' provides an interface to 'SyncroSim'. Simulation models can be added to 'SyncroSim' in order to transform these datasets, taking advantage of general features such as defining scenarios of model inputs, running Monte Carlo simulations, and summarizing model outputs. 'rsyncrosim' requires 'SyncroSim' 2.3.5 or higher (API documentation: <https://docs.syncrosim.com/>).

rsyncrosim

The R interface to SyncroSim

License:MIT Downloads

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About SyncroSim

SyncroSim is a software platform that helps you turn your data into forecasts. At the core of SyncroSim is an engine that automatically structures your existing data, regardless of its original format. SyncroSim transforms this structured data into forecasts by running it through a Pipeline of calculations (i.e. a suite of models). Finally, SyncroSim provides a rich interface to interact with your data and models, allowing you to explore and track the consequences of alternative “what-if” forecasting Scenarios. Within this software framework is the ability to use and create SyncroSim packages.

For more details consult the SyncroSimonline documentation.

About rsyncrosim

The simplest way to run SyncroSim from the command-line is to use the R programming language, in conjunction with the open-source rsyncrosim R package. This R package is designed to make it simple to script modeling workflows for SyncroSim in R, by providing functions that allow users to create models from scratch, populate those models with inputs, run the models for multiple scenarios, and access both spatial and tabular model output. The package is designed to work with any SyncroSim Package.

A key feature of the rsyncrosim package is its ability to work seamlessly with the SyncroSim user interface. By integrating model scripting and visualization, users can interactively explore and validate their models in the user interface as they step through their R code, and at the same time generate a permanent, repeatable record of their entire modeling workflow – including both pre- and post-processing of model inputs and outputs – in an R script.

Installation

Getting Started

Metadata

Version

1.5.0

License

Unknown

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