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This is due to the random character of the bootstrapping: each time you sample from the original data, the random samples will be different unless you provide the same setting of the random number generator each time.
You can use set.seed(<SOME INTEGER>)
to feed the random number generator with the same starting conditions each time; then you will retrieve exactly the same results for each run of dcc()
and seascorr()
given unchanged data.
No, this minimum number of observations is requested for the exact bootstrapping to work.
Please check the reference manual. If method XY is not mentioned there, it is not supported. To file a feature request, please use https://github.com/cszang/treeclim/issues.
Please file a bug report at https://github.com/cszang/treeclim/issues.
Please please ask on the mailing list https://groups.google.com/forum/#!forum/treeclim. Not that I would expect volunteers to help ;-) but it will help me to point you to already existing answers and to identify FAQs.