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The standard plot for field verification (e.g. Fig 7 of Hakim et al 2016) gives no indication of significance. Yet, because of persistence and the relatively low # of degrees of freedom, r values well above 0 might be statistical artifacts.
I suggest re-using the correlation function from Pyleoclim's Stats.py to test for this, and covering all the areas of the graph that are not significant at the 5% level with black dots.
The code is written in Python 3.5, so it may make sense to wait until LMR moves to Python 3 world.
The text was updated successfully, but these errors were encountered:
The standard plot for field verification (e.g. Fig 7 of Hakim et al 2016) gives no indication of significance. Yet, because of persistence and the relatively low # of degrees of freedom, r values well above 0 might be statistical artifacts.
I suggest re-using the correlation function from Pyleoclim's Stats.py to test for this, and covering all the areas of the graph that are not significant at the 5% level with black dots.
The code is written in Python 3.5, so it may make sense to wait until LMR moves to Python 3 world.
The text was updated successfully, but these errors were encountered: