Energy consumption estimates generated in RPSS analyses were consistently greater than estimates generated by the baseline deterministic model, which used the parameter values from Table 1.
RPSS decreased, especially for females), but also projected higher energy consumption rates.
Estimates from the RPSS analysis were determined at three levels of parameter uncertainty, with parameter coefficients of variation (CV) equal to 2, 10, or 20%.
To test Hypothesis 3 that Collaborative RPSS predicts incremental variance beyond each of the three coping styles, three separate hierarchical regression analyses were conducted.
Principal axis factor analysis followed by an oblique rotation was used to ascertain that the original factor structure of RPSS replicated in the population of people who have severe mental illnesses.
When statistically separated from the Collaborative RPSS, consistent with Hypothesis 2, use of the Deferring RPSS predicted less active pursuit of recovery.
RPSS indicate the variance in mean profit per dive (joules) explained by variation in each parameter, with effects of the other parameters statistically removed.
Regarding search and handling parameters, effects of varying the functional response coefficients were relatively negligible in Vallisneria habitats (Table 3); however, RPSS and partial [r.
The probabilistic WFIP ensemble ramp predictions resulted in a large (20% or more) improvement in the
RPSS as compared with the baseline (ELRAS) forecasts.
Figure 8 shows the spatial distribution of RPSS for hindcasts of precipitation for DJF (initialized in July) over North America using the multimodel ensemble (left) and CFSv2 alone (right).
Overall, the various skill metrics (correlation, RMSE, RPSS, and reliability) all suggest that the NMME system improves the skill over the CFSv2.
They repeated and confirmed the
RPSS calculations to provide independent verification of the Aquila forecast rankings.
