Search by property

From CSDMS

This page provides a simple browsing interface for finding entities described by a property and a named value. Other available search interfaces include the page property search, and the ask query builder.

Search by property

A list of all pages that have property "Extended model description" with value "Dakota is a software toolkit, developed at Sandia National Laboratories, that provides an interface between models and a library of analysis methods, including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. Dakotathon is a Python package that wraps and extends Dakota’s file-based user interface. It simplifies the process of configuring and running a Dakota experiment, and it allows a Dakota experiment to be scripted. Any model written in Python that exposes a Basic Model Interface (BMI), as well as any model componentized in the CSDMS modeling framework, automatically works with Dakotathon. Currently, six Dakota analysis methods have been implemented from the much larger Dakota library: * vector parameter study, * centered parameter study, * multidim parameter study, * sampling, * polynomial chaos, and * stochastic collocation.". Since there have been only a few results, also nearby values are displayed.

Showing below up to 2 results starting with #1.

View (previous 50 | next 50) (20 | 50 | 100 | 250 | 500)


    

List of results

    • Model:Dakotathon  + (Dakota is a software toolkit, developed atDakota is a software toolkit, developed at Sandia National Laboratories, that provides an interface between models and a library of analysis methods, including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. Dakotathon is a Python package that wraps and extends Dakota’s file-based user interface. It simplifies the process of configuring and running a Dakota experiment, and it allows a Dakota experiment to be scripted. Any model written in Python that exposes a Basic Model Interface (BMI), as well as any model componentized in the CSDMS modeling framework, automatically works with Dakotathon. Currently, six Dakota analysis methods have been implemented from the much larger Dakota library:</br></br>* vector parameter study,</br>* centered parameter study,</br>* multidim parameter study,</br>* sampling,</br>* polynomial chaos, and</br>* stochastic collocation.omial chaos, and * stochastic collocation.)