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(BUG) L function and its Simulation Envelope under the null (CSR) not close to 0 #44
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I think the equation is implemented incorrectly.. It should read: support, kestimate = _k(pp, intervals, dmin, dmax, d).T
lestimate = np.sqrt(kestimate / np.pi)
return np.column_stack((support, lestimate)) |
FWIW, this is the formulation found in O’Sullivan and Unwin (2010). I was going to add it into
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I do not see a major difference between these two implementations - the only difference is that your implementation does not deduct the distance from the "normalized" L function. The current implementation in We have found the bug and Serge has fixed it in #45. Another bug is introduced with this PR and it is supposed to be fixed in #46. I should have closed this issue (have been waiting for the close of the #46) - sorry if this induces any confusion. |
I see! Feel free to close this then!
Right. The plotting correction is not the L function itself. I understand the L with this adjustment is interpreted like the J but centered on zero. I think this needs to be documented + given an option. |
The equation is given in the example notebook for distance statistics. I will add the missing equations for the distance functions to the inline docstrings. Thanks for the suggestion. |
This issue is raised by a user of
pointpats
- Wei Xie.The Simulation Envelope under the null of CSR built for the L function is nowhere near 0 (see the following figure), which is not right based on its definition.
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