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- W2188045863 abstract "Simulation models for agriculture and natural resource management are widely promoted as powerful tools for research and decision support. Before applying a model, users should understand how well the model represents the processes of interest and how accurate the outputs are likely to be. Many model validation procedures are based on comparison of observed and simulated data. Advances in statistical methods and computer capabilities offer numerous options for strengthening model validation. This report describes the development of an interface that permits the analysis of simulation models using statistical methods. A number of statistical methods are currently available, including regression techniques, such as linear regression (r2, slope, and intercept), quantile regression, and the simultaneous FTest. The PyRamid application has been created as a prototype for producing a convenient way for researchers to apply these regression techniques. PyRamid was developed in Python and exploits the RPy interface to R to execute R functions and access R’s graphing capabilities through an easy to use graphical interface. Future work includes adding visual techniques and deviance measures, such as mean absolute error, root mean squared deviation, and modeling efficiency, into PyRamid’s list of capabilities." @default.
- W2188045863 created "2016-06-24" @default.
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- W2188045863 date "2006-01-01" @default.
- W2188045863 modified "2023-09-27" @default.
- W2188045863 title "Implementation of a Python - R interface for the asses s me nt of simulation models" @default.
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