kernel_dispersion {tectonicr} | R Documentation |
Adaptive Kernel Dispersion
Description
Stress field and wavelength analysis using circular dispersion (or other statistical estimators for dispersion)
Usage
kernel_dispersion(
x,
stat = c("dispersion", "nchisq", "rayleigh"),
grid = NULL,
lon_range = NULL,
lat_range = NULL,
gridsize = 2.5,
min_data = 3L,
max_data = Inf,
min_dist_threshold = 200,
dist_threshold = 0.1,
stat_threshold = Inf,
R_range = seq(100, 2000, 100),
...
)
dispersion_grid(...)
Arguments
x |
|
stat |
The measurement of dispersion to be calculated. Either
|
grid |
(optional) Point object of class |
lon_range , lat_range |
(optional) numeric vector specifying the minimum
and maximum longitudes and latitudes (are ignored if |
gridsize |
Numeric. Target spacing of the regular grid in decimal
degree. Default is 2.5. (is ignored if |
min_data |
Integer. Minimum number of data per bin. Default is |
max_data |
integer. The number of nearest observations that should be
used for prediction, where "nearest" is defined in terms of the space of the
spatial locations. Default is |
min_dist_threshold |
Numeric. Maximum distance (in km) of the grid point to the next data point. Default is 200 |
dist_threshold |
Numeric. Distance weight to prevent overweight of data
nearby ( |
stat_threshold |
numeric. Generates missing values when the kernel
|
R_range |
Numeric value or vector specifying the (adaptive) kernel
half-width(s) as search radius (in km). Default is |
... |
optional arguments to |
Value
sf
object containing
- lon,lat
longitude and latitude in degree
- stat
output of function defined in
stat
- R
The rearch radius in km.
- mdr
Mean distance of datapoints per search radius
- N
Number of data points in search radius
Note
dispersion_grid()
was renamed to kernel_dispersion()
to create
a more consistent API.
See Also
circular_dispersion()
, norm_chisq()
, rayleigh_test()
Examples
data("nuvel1")
PoR <- subset(nuvel1, nuvel1$plate.rot == "na")
san_andreas_por <- san_andreas
san_andreas_por$azi <- PoR_shmax(san_andreas, PoR, "right")$azi.PoR
san_andreas_por$prd <- 135
kernel_dispersion(san_andreas_por) |> head()