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Description
This is an arid basin with long periods of no flow. In such cases the standard deviation of certain years is 0 and the correlation for such years is undefined. As a result, all metrics are calculated (partly) on NaN values and return NA.
I don't know if any clear solutions exist to make the computations succeed in these cases (maybe just hard-code solutions for the specific cases where obs and/or sim are all zero, or try to detect these and exit with a specific message?), but it seemed good to document this behaviour at least.
GOF_stat seJack seBoot p05 p50 p95 score biasJack biasBoot seJab
1 NA NA NA NA NA NA NA NA NA
Warning messages:
1: In bootjack(df) : NAs introduced by coercion
2: In bootjack(df) : NAs introduced by coercion
3: In bootjack(df) : NAs introduced by coercion
The text was updated successfully, but these errors were encountered:
Thanks for finding this. I'll get to it when I can, but won't be able to do anything until June.
It might be possible to use na.rm = TRUE for some functions, but it might not work for everything.
Description
This is an arid basin with long periods of no flow. In such cases the standard deviation of certain years is 0 and the correlation for such years is undefined. As a result, all metrics are calculated (partly) on NaN values and return
NA
.I don't know if any clear solutions exist to make the computations succeed in these cases (maybe just hard-code solutions for the specific cases where
obs
and/orsim
are all zero, or try to detect these and exit with a specific message?), but it seemed good to document this behaviour at least.Sample data: gumboot_issue.csv
Sample code
Output
The text was updated successfully, but these errors were encountered: