(a)-(b) are generated using the fidelity, F, and (c)-(d) using the Kolmogorov distance, K, for nearest neighbor distances and angles respectively. Stochasticity was introduced in the model through drawing the parameter Du and Ds in the differential equations Eqs 1–4 from a normal distribution with varying standard deviation, σ, and mean value, μ. The simulation results were compiled, and nearest R8 cell neighbor angle and distance distributions were obtained. Kolmogorov and fidelity of the resulting distributions where computed with reference to the perfect pattern case. Here, a value of 1 corresponds to a perfectly ordered pattern, and a value of 0 corresponds to a completely irregular pattern. This figure illustrates that the functional f...
Van Lieshout and Baddeley introduced the function J = (1 \Gamma G)=(1 \Gamma F ) as a measure of int...
This paper proposes a new methodology for computing Hausdorff distances between sets of points in a ...
The analysis is applied in the same setting as Fig 9, i.e. stochasticity is introduced in the diffus...
Stochasticity was introduced in the differential equations by drawing the value of the diffusion coe...
Distances are naturally binned by the available sites on the underlying hexagonal lattice, whereas a...
Here, the variance of the distributions of (a) nearest neighbor distances and (b) nearest neighbor a...
<p>(A–C) Probability distribution of the time interval for the PGC (posterior-most green cells) in t...
Distance transforms (DTs) are standard tools in image analysis, with applications in image registrat...
Let N points be uniformly randomly distributed in a d-dimensional ball of radius R, centered at the ...
Consider an unlimited homogeneous medium disturbed by points generated via Poisson process...
In this paper we define distance functions for data sets (and distributions) in a RKHS context. To ...
The analysis of spatial point patterns is commonly focused on the distances to the nearest neighbor....
Three functions that analyze point patterns are the L (a transformation of Ripley’s K function), pai...
The analysis of point patterns often begins with a test of complete spatial randomness using summari...
The local order measure is calculated as a function of position, from posterior to anterior. The x-a...
Van Lieshout and Baddeley introduced the function J = (1 \Gamma G)=(1 \Gamma F ) as a measure of int...
This paper proposes a new methodology for computing Hausdorff distances between sets of points in a ...
The analysis is applied in the same setting as Fig 9, i.e. stochasticity is introduced in the diffus...
Stochasticity was introduced in the differential equations by drawing the value of the diffusion coe...
Distances are naturally binned by the available sites on the underlying hexagonal lattice, whereas a...
Here, the variance of the distributions of (a) nearest neighbor distances and (b) nearest neighbor a...
<p>(A–C) Probability distribution of the time interval for the PGC (posterior-most green cells) in t...
Distance transforms (DTs) are standard tools in image analysis, with applications in image registrat...
Let N points be uniformly randomly distributed in a d-dimensional ball of radius R, centered at the ...
Consider an unlimited homogeneous medium disturbed by points generated via Poisson process...
In this paper we define distance functions for data sets (and distributions) in a RKHS context. To ...
The analysis of spatial point patterns is commonly focused on the distances to the nearest neighbor....
Three functions that analyze point patterns are the L (a transformation of Ripley’s K function), pai...
The analysis of point patterns often begins with a test of complete spatial randomness using summari...
The local order measure is calculated as a function of position, from posterior to anterior. The x-a...
Van Lieshout and Baddeley introduced the function J = (1 \Gamma G)=(1 \Gamma F ) as a measure of int...
This paper proposes a new methodology for computing Hausdorff distances between sets of points in a ...
The analysis is applied in the same setting as Fig 9, i.e. stochasticity is introduced in the diffus...