qnn.test calculates statistics related to the q
nearest neighbors method of comparing case and control
point patterns under the random labeling hypothesis.
qnn.test(x, q = 5, nsim = 499, case = 2, longlat = FALSE)A ppp object from the spatstat
package with marks for the case and control groups.
A vector of positive integers indicating the
values of q for which to do the q nearest
neighbors test.
The number of simulations from which to compute p-value.
The position of the name of the "case" group in levels(x$marks). The default is 2.
A logical value indicating whether
Euclidean distance (FALSE) or Great Circle
(WGS84 ellipsoid, FALSE) should be used.
Default is FALSE, i.e., Euclidean distance.
Returns a list with the following components:
A dataframe with the number of neighbors (q), test statistic (Tq), and p-value for each test.
A dataframe with the contrasts (contrast), test statistic (Tcon), and p-value (pvaluecon) for the test of contrasts.
Waller, L.A., and Gotway, C.A. (2005). Applied Spatial Statistics for Public Health Data. Hoboken, NJ: Wiley.
Cuzick, J., and Edwards, R. (1990). Spatial clustering for inhomogeneous populations. Journal of the Royal Statistical Society. Series B (Methodological), 73-104.
Alt, K.W., and Vach, W. (1991). The reconstruction of "genetic kinship" in prehistoric burial complexes-problems and statistics. Classification, Data Analysis, and Knowledge Organization, 299-310.
# NOT RUN {
data(grave)
qnn.test(grave, q = c(3, 5, 7, 9, 11, 13, 15))
# }
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