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Spatial Point Patterns
book

Spatial Point Patterns

by Adrian Baddeley, Ege Rubak, Rolf Turner
November 2015
Intermediate to advanced content levelIntermediate to advanced
828 pages
33h 11m
English
Chapman and Hall/CRC
Content preview from Spatial Point Patterns
Intensity 167
> quadrat.test(Q3)
Chi-squared test of CSR using quadrat counts
Pearson X2 statistic
data:
X2 = 4.7, df = 8, p-value = 0.4
alternative hypothesis: two.sided
Quadrats: 3 by 3 grid of tiles
The results of several quadrat tests can also be pooled. For example, suppose an ecologist has
recorde d the spatial pattern of trees in three separate plots in the same forest. The data from each
plot have been subje c te d to a quadrat c ounting test as described above. Then an overall test of
unifor m intensity is performed by applying pool.quadrattest to the three test results:
test1 <- quadrat.test(X1, 3)
test2 <- quadrat.test(X2, 3)
test3 <- quadrat.test(X3, 5)
pool(test1, test2, test3)
The qua drat test of homogeneity can be gen e ralised to a test
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Publisher Resources

ISBN: 9781482210217