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Understanding Dominant Factors for Precipitation over the Great Lakes Region
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use only the dominant factors selected by LASSO plus permutation test instead of all covariates (ablation) | OLS regression · East-North-Central, Central, North-East | RMSE: 50.76 -> 50.38 (ENC); 53.29 -> 52.12 (Central); 67.04 -> 67.51 (North-East) | No clear effect |
| use dominant factors (fewer than 25 per region) instead of the full pool of 232 predictors (ablation) | OLS regression · Great Lakes regions | number of predictors: 232 -> less than 25 | Helped |
| add dominant climate factors as predictors versus predicting the climatological mean | OLS regression · East-North-Central | RMSE: 66.26 -> 50.38 | Helped |
| add dominant climate factors as predictors versus predicting the climatological mean | OLS regression · Central | RMSE: 61.66 -> 52.12 | Helped |
| add dominant climate factors as predictors versus predicting the climatological mean | OLS regression · North-East | RMSE: 86.95 -> 67.51 | Helped |
| move from inland regions (Central, ENC) to the North-East region | OLS on dominant factors · Great Lakes stations | RMSE: 50.38 -> 67.51 | Hurt |
| choose lambda using a 2% validation split of the training set with smallest validation MSE | LASSO · Dominant factor selection | validation MSE | Helped |
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