v.nnstat input=rand_2000_2d
Input coordinates have been read... Computing average distance between nearest neighbors... 100% *** Nearest Neighbour Analysis results *** Input settings .. 3D layer: 0 3D NNA: 0 Number of points .......... 2000 Area ...................... 398645718.651701 [units^2] Density of points ......... 0.000005 Average distance between the nearest neighbours ........... 225.859 [units] Average expected distance between the nearest neighbours .. 223.228 [units] Ratio rA/rE ............... 1.011785 *** Results of two-tailed test of the mean *** Null hypothesis: Point set is randomly distributed within the region. Standard variate of the normal curve> c = 1.008239 Null hypothesis IS NOT REJECTED at the significance level alpha = 0.05 |
v.nnstat input=rand_2000_3d -2
Input coordinates have been read... Computing average distance between nearest neighbors... 100% *** Nearest Neighbour Analysis results *** Input settings .. 3D layer: 1 3D NNA: 0 Number of points .......... 2000 Area ...................... 398645718.651701 [units^2] Density of points ......... 0.000005 Average distance between the nearest neighbours ........... 225.859 [units] Average expected distance between the nearest neighbours .. 223.228 [units] Ratio rA/rE ............... 1.011785 *** Results of two-tailed test of the mean *** Null hypothesis: Point set is randomly distributed within the region. Standard variate of the normal curve> c = 1.008239 Null hypothesis IS NOT REJECTED at the significance level alpha = 0.05 |
NOTE: Comparing the results of 2D NNA with results summarized in (Stopkova, 2013), there can be seen small difference between the values of area. It is assumed to be caused by differences in transformed coordinates of the convex hull that have been computed using two versions of the module.
v.nnstat input=rand_2000_3d
Input coordinates have been read... Computing average distance between nearest neighbors... 100% Reading 3D vertices... 100% Constructing 3D hull... 99% *** Nearest Neighbour Analysis results *** Input settings .. 3D layer: 1 3D NNA: 1 Number of points .......... 2000 Volume .................... 398423031180.489197 [units^3] Density of points ......... 0.000000 Average distance between the nearest neighbours ........... 346.072 [units] Average expected distance between the nearest neighbours .. 323.531 [units] Ratio rA/rE ............... 1.069670 *** Results of two-tailed test of the mean *** Null hypothesis: Point set is randomly distributed within the region. Standard variate of the normal curve> c = 0.191691 Null hypothesis IS NOT REJECTED at the significance level alpha = 0.05 |
v.nnstat input=rand_2000_2d zcolumn=z
Reading elevations from attribute table: 2000 records selected Input coordinates have been read... Computing average distance between nearest neighbors... 100% Reading 3D vertices... 100% Constructing 3D hull... 99% *** Nearest Neighbour Analysis results *** Input settings .. 3D layer: 0 .. 3D NNA: 1 .. zcolumn: z Number of points .......... 2000 Volume .................... 398423031180.489197 [units^3] Density of points ......... 0.000000 Average distance between the nearest neighbours ........... 346.072 [units] Average expected distance between the nearest neighbours .. 323.531 [units] Ratio rA/rE ............... 1.069670 *** Results of two-tailed test of the mean *** Null hypothesis: Point set is randomly distributed within the region. Standard variate of the normal curve> c = 0.191691 Null hypothesis IS NOT REJECTED at the significance level alpha = 0.05 |
In (Stopkova, 2013), there might be seen other examples (also clustered and dispersed datasets).
Available at: v.nnstat source code (history)
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