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Complete and spatial likelihood results for the forecasts of the EAST ∗EEPAS, linear combination EAST+EEPAS (half and half), EAST R, EEPAS, and RI reference models.
Examples of the L-test and BS-test are depicted in Figs. 8 and 9 for the forecasts of three experiments from 2006 to 2009, respectively.
For the forecasts of other factors (e.g. employment), according to option B, the new vector of sectoral employment due to the new final demand vector f 1 is derived as e B = π ¯ ˆ x ¯ B = π ¯ ˆ L ¯ p ˆ f f 1. (8).
The prognostic parameters estimated for the forecasts of the neural networks were characterised by lower errors of prediction for both the daily yields and test-day data and exhibited higher coefficients of correlation between the predicted and the actual data (or the yields produced by SYMLEK).
These correlations are relevant for the results published for the EEA+ as a whole, not for the forecasts of the individual countries.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com