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