I am analyzing a point pattern using G (nearest neighbor cumulative distribution) function, followed up by the envelope tests and in the same time using Nearest Neighbor Index test (Clark Evans test ). For this purpose I use spatstat, guided by "Spatial Point Patterns: Methodology and Applications with R" by Baddeley, Rubak and Turner.
To my surprise the G tests results in non rejection of the H0, while Clark Evans test suggests rejection of the H0. I was wondering if it means that one of the tests for any reason provides false result? or that due to the nature of the tests there is no fallacy in observing such results.
Another question: could Clark Evans test be used to test not only CSR, but other H0?
Thank you!
update:
Here is an example of the spatial pattern
further:
plot(envelope(my_pattren, Gest, correction="none"))
results of MAD test
mad.test(my_pf[[33]], Gest)
Monte Carlo test based on 99 simulations
Summary function: G(r)
Reference function: theoretical
Alternative: two.sided
Interval of distance values: [0, 77.6841825602024]
Test statistic: Maximum absolute deviation
Deviation = observed minus theoretical
data: my_pattern
mad = 0.36677, rank = 19, p-value = 0.19
Clark Evans test
clarkevans.test(my_pattern)
Clark-Evans test
No edge correction
Z-test
data: my_pattern
R = 1.2298, p-value = 0.03502
alternative hypothesis: two-sided
mad.test
onmy_pf[33]]
andclarkevans.test
onmy_pattern
? Also did you try to add a correction toclarkevans.test
? The uncorrected index tends to be positively biased and may lead to spurious results. $\endgroup$ – Ege Rubak Sep 21 '17 at 8:04