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Tutorials

Jupyter Notebooks for tutorials of scores.

Firstly run Data Fetching to fetch the data needed for some later notebooks

Data Fetching

Continuous

Additive Bias, Multiplicative Bias and Percent Bias

MAE

RMSE

MSE

Percent within X

Nash–Sutcliffe Model Efficiency Coefficient (NSE)

Pearson's Correlation

Spearman's Correlation

Kling-Gupta Efficiency

Quantile Loss

Flip-Flop Index

Consistent Scores

Threshold Weighted Scores

Quantile Interval Score and Interval Score

Probability

Brier Score

CRPS for Forecasts Expressed as CDFs

CRPS for Ensemble Forecasts

twCRPS for Ensemble Forecasts

Probability Integral Transform (PIT)

Relative Economic Value

Categorical

Binary (Categorical/Contingency/Confusion Matrix) Scores

FIRM

Risk Matrix Score

SEEPS

Spatial

Fractions Skill Score

Statistical Tests

Diebold Mariano

Processing

Weighting Results

Isotonic Regression and Reliability Diagrams

Block Bootstrapping

Plotting Data

Murphy Diagrams

Q-Q plots

Rank Histogram

Receiver Operating Characteristic (ROC)

Other

Dimension Handling

Angular Data

Introduction to Pandas API