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 720 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: 720 × 7
#>      lon   lat    stat     R    mdr     N        geometry
#>  * <dbl> <dbl>   <dbl> <dbl>  <dbl> <int>     <POINT [°]>
#>  1 -115.  24.3 NA        100 NA         0 (-114.57 24.33)
#>  2 -115.  24.3 NA        200 NA         1 (-114.57 24.33)
#>  3 -115.  24.3  0.0144   300  0.683     3 (-114.57 24.33)
#>  4 -115.  24.3  0.0173   400  0.654     6 (-114.57 24.33)
#>  5 -115.  24.3  0.0561   500  0.896    90 (-114.57 24.33)
#>  6 -115.  24.3  0.0519   600  0.817   153 (-114.57 24.33)
#>  7 -115.  24.3  0.0557   700  0.737   183 (-114.57 24.33)
#>  8 -115.  24.3  0.0571   800  0.653   188 (-114.57 24.33)
#>  9 -115.  24.3  0.0576   900  0.608   203 (-114.57 24.33)
#> 10 -115.  24.3  0.0637  1000  0.590   228 (-114.57 24.33)
#> # ℹ 710 more rows

Usage

Arguments

Value

See also

Examples