Downloads provided by UsageCounts
These files contain the scripts and data for reproducing the results of the article "Evaluating the predictive performance of presence-absence models: why can the same model appear excellent or poor?". These scrips compute four metrics (AUC, Tjurs R2, max-Kappa and max-TSS) measuring the predictive performance of presence absence models applied to a fungal dataset (Fungi_data.csv). To compare the metrics, these are applied at different spatial hierarchical scales and using different cross validation strategies. The scrips should be used in R and in the following order: (1) S1 Define models, (2) S2_1 Fit models and evaluates AUC TjurR2, (3) S2_2 Add Kappa tss, (4) S2_3 Average replicates, (5) S3 Show examples Fig. 1, (6) S4 Show relationships among measures, (7) S5 Show hierarchical results Fig.3.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 16 | |
| downloads | 16 |

Views provided by UsageCounts
Downloads provided by UsageCounts