Adaptive Kernel Dispersion

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 = 3,
  threshold = 1,
  arte_thres = 200,
  dist_threshold = 0.1,
  R_range = seq(100, 2000, 100),
  ...
)

Arguments

x

sf object containing

azi: Azimuth in degree
unc: Uncertainties of azimuth in degree
prd: Predicted value for azimuth

stat

The measurement of dispersion to be calculated. Either "dispersion" (default), "nchisq", or "rayleigh" for circular dispersion, normalized Chi-squared test statistic, or Rayleigh test statistic.

grid

(optional) Point object of class sf.

lon_range, lat_range

(optional) numeric vector specifying the minimum and maximum longitudes and latitudes (are ignored if "grid" is specified).

gridsize

Numeric. Target spacing of the regular grid in decimal degree. Default is 2.5. (is ignored if "grid" is specified)

min_data

Integer. Minimum number of data per bin. Default is 3

threshold

Numeric. Threshold for stat value (default is 1)

arte_thres

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 (0 to 1). Default is 0.1

R_range

Numeric value or vector specifying the (adaptive) kernel half-width(s) as search radius (in km). Default is seq(50, 1000, 50)

...

optional arguments to dist_greatcircle()

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

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)
#> Simple feature collection with 800 features and 6 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: -124.57 ymin: 24.33 xmax: -107.07 ymax: 39.33
#> Geodetic CRS:  WGS 84
#> # A tibble: 800 × 7
#>      lon   lat    stat     R     N    mdr        geometry
#>  * <dbl> <dbl>   <dbl> <dbl> <int>  <dbl>     <POINT [°]>
#>  1 -115.  24.3 NA        100     0 NA     (-114.57 24.33)
#>  2 -115.  24.3 NA        200     1 NA     (-114.57 24.33)
#>  3 -115.  24.3  0.230    300     4  0.743 (-114.57 24.33)
#>  4 -115.  24.3  0.111    400    18  0.816 (-114.57 24.33)
#>  5 -115.  24.3  0.0774   500   109  0.878 (-114.57 24.33)
#>  6 -115.  24.3  0.0717   600   175  0.801 (-114.57 24.33)
#>  7 -115.  24.3  0.0728   700   206  0.723 (-114.57 24.33)
#>  8 -115.  24.3  0.0733   800   212  0.641 (-114.57 24.33)
#>  9 -115.  24.3  0.0749   900   236  0.609 (-114.57 24.33)
#> 10 -115.  24.3  0.0646  1000   306  0.642 (-114.57 24.33)
#> # ℹ 790 more rows

Usage

Arguments

Value

See also

Examples