File Exchange

image thumbnail


version 1.1.0 (3.71 KB) by K NARENDER REDDY
The Willmott index is a more advanced method to evaluate the land surface model performance than traditionally used methods: r, r2, etc.


Updated 06 May 2021

From GitHub

View Version History

View license on GitHub

Pearson correlation coefficient (r), coefficient of determination (r2), mean absolute error (MAE), root mean square error (RMSE), and other statistical methods are commonly used to compare model output with observed results. Traditional approaches aren't always the best for assessing model–data agreement or disagreement. The r or r2 methods, for example, can show the overall linear covariation between data and model results, but they must be combined with the slope and intercept of the linear regression to determine the degree to which the observed results are captured by the model. Willmott's index, on the other hand, is sensitive to variations between measured and modeled values and can reflect the degree to which the model can capture measured variance.

Cite As

K NARENDER REDDY (2021). willmontt_index (, GitHub. Retrieved .

Comments and Ratings (0)

MATLAB Release Compatibility
Created with R2021a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Tags Add Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!