max_kernel_sd_det: Maximum kernel standard deviation for the Gaussian...
In adchSTATS/icpp: Simulate a limiting iterated cluster point process

Description Usage Arguments Details Value

The Gaussian determinantal point process is specified by a zero-mean Guassian density function, more generally refered to as the kernel function.

1	max_kernel_sd_det(int, check = FALSE)

`int`	The intensity of the point pattern.
`check`	If `FALSE` a rounded value is returned. This ensures that the value will pass a check of whether the value is appropriate. If thrue a non-rounded value is returned, which can be used to ensure that the condition is satisfied.

The variance determines the 'interaction radius' between points. Large values of this variance means more repulsion for the weighted determinantal point process and more clustering for the weighted permanental point process. It has a maximum for the determinantal point process that depends on the intensity, in order to ensure existence of the process. The more points the less regularity is obtainable.

The maximal value of the kernel standard deviation, under the determinantal point process.

adchSTATS/icpp documentation built on May 28, 2019, 3:54 p.m.