A parity plot is a scatterplot that compares a set of results from a computational model against benchmark data. Each point has coordinates (x, y), where x is a benchmark value and y is the corresponding value from the model.[1]

A line of the equation y = x, representing perfect model performance, is sometimes added as a reference. Where the model successfully reproduces a benchmark, that point will lie on the line.

Parity plots are found in scientific papers and reports, when the author wishes to validate a model in a visual way. However, when the data have a wide range, the large scale makes important discrepancies invisible and the model appears better than it actually is. In that case, a plot of model errors [(y − x) vs. x] is better for evaluating the performance of the model.

See also

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References

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  1. ^ Rhinehart, R. R. (2016). Nonlinear Regression Modeling for Engineering Applications: Modeling, Model Validation, and Enabling Design of Experiments. Deutschland: Wiley. Page 251 https://www.google.de/books/edition/Nonlinear_Regression_Modeling_for_Engine/LonIDAAAQBAJ?hl=de&gbpv=1&dq=%22parity%20plot%22%20definition%20statistic&pg=PA251


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