Framework library releases
Releases of foundation and authoring tools libraries to implement the ready4 framework.
Tag: Framework
Installing the ready4 framework foundation library
The ready4 framework foundation is the first ready4 library you should install.
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Installing tools for authoring model modules
Instructions for installing the ready4class, ready4fun and ready4pack libraries.
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Framework taxonomies dataset releases
Releases of the dataset of taxonomies used to help standardise code authoring and documentation.
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Installing tools for authoring and managing model datasets
Instructions for installing the ready4use library.
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Installing authoring tools
Depending on how you plan to use ready4, you may need to install some or all of its authoring tools.
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Installing tools for authoring reproducible analyses
Instructions for installing the ready4show library.
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Authoring ready4 modules
Tools from the ready4class, ready4 fun and ready4pack R packages streamline and standardise the authoring of ready4 modules.
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Framework
The ready4 framework comprises a set of standards and the software to implement it.
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Standards
The ready4 framework identifies a set of standards to which the ready4 model, its datasets and analyses are expected to adhere.
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Implementation
The software to help ensure that the ready4 model adheres to consistent standards is distributed as a collection of framework code libraries.
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Paradigms
ready4 software is implemented using a combination of object-oriented and functional programming paradigms.
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Why ready4 is object oriented
ready4 uses an object oriented programming (OOP) paradigm to implement computational models.
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The role of functional programming in ready4 development
ready4 uses functional programming to maximise the re-usability of model algorithms.
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Modularity
ready4 supports a modular approach to computational model development.
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Syntax
ready4 modules use a simple and consistent syntax.
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Authoring model data
The ready4use R package provides tools for supplying data to youth mental health computational models.
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Search open access data collections
Online open access data repositories are the preferred storage locations for ready4 model datasets.
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Share data via online repositories
The retrieval and dissemination of data from online data repositories is an essential enabler of open source modelling. This tutorial describes how a module from the ready4use R package can help you to manage this process.
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Ingest data from an open access repository
A tutorial from the Acumen website about using ready4 to search and retrieve data from the Australian Mental Health Systems Models Dataverse.
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Add a data dictionary to a dataset
Pairing a dataset with its dictionary makes it easier to interpret. This tutorial describes how a module from the ready4use R package can help you to pair a dataset and its dictionary.
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Framework libraries
There are two types of framework libraries - a foundational library and libraries of authoring tools.
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Introducing ready4 framework modules and syntax
Announcing the introduction of a novel approach to developing modular models with a simple, consistent syntax.