spline.correlog2D() R function from [ncf]

Anisotropic nonparametric (cross-)correlation function for univariate spatial data

spline.correlog2D is the function to estimate the anisotropic nonparametric correlation function in 8 (or arbitrary) directions (North - Southeast) for univariate data. Correlation functions are calculated for each different bearing. The function assumes univariate observations at each location. (use Sncf2D otherwise).


spline.correlog2D(
  x,
  y,
  z,
  w = NULL,
  df = NULL,
  type = "boot",
  resamp = 1000,
  npoints = 300,
  save = FALSE,
  max.it = 25,
  xmax = FALSE,
  na.rm = FALSE,
  jitter = FALSE,
  quiet = FALSE,
  angle = c(0, 22.5, 45, 67.5, 90, 112.5, 135, 157.5)
)

Arguments

x: vector of length n representing the x coordinates.
y: vector of length n representing the y coordinates.
z: vector of length n representing the observation at each location.
w: an optional second vector of length n for variable 2 (to estimate spatial or lagged cross-correlation functions).
df: degrees-of-freedom for the spline. Default is sqrt(n).
type: takes the value "boot" (default) to generate a bootstrap distribution or "perm" to generate a null distribution for the estimator
resamp: the number of resamples for the bootstrap or the null distribution.
npoints: the number of points at which to save the value for the spline function (and confidence envelope / null distribution).
save: If TRUE, the whole matrix of output from the resampling is saved (an resamp x npoints dimensional matrix).
max.it: the maximum iteration for the Newton method used to estimate the intercepts.
xmax: If FALSE, the max observed in the data is used. Otherwise all distances greater than xmax is omitted.
na.rm: If TRUE, NA's will be dealt with through pairwise deletion of missing values for each pair of time series -- it will dump if any one pair has less than two (temporally) overlapping observations.
jitter: If TRUE, jitters the distance matrix to avoid problems associated with fitting the function to data on regular grids.
quiet: If TRUE, the counter is suppressed during execution.
angle: specifies number of cardinal directions and angles for which to calculate correlation functions. Default are 8 directions between 0 and 180.

Returns

An object of class "Sncf2D" is returned. See Sncf2D for details.

Details

see Sncf2D

Note

The function to estimate the UNIvariate anisotropic nonparametric (cross-)correlation function in arbitrary directions. In particular it was developed to calculate the univariate lagged cross-correlation function used in (Humston et al. 2005). Note that this 2D spline correlogram does the anisotropic analysis NOT by doing the angle-with-tolerance-wedge-style of Oden and Sokal (1986) but by projecting the the spatial coordinates of all locations on a sequence of cardinal angles (a la Sncf2D). Hence, all data points are used every time, it is only their relative distances that are changed. For example {0, 0} and {0, 10} are distance zero in the zero-degree direction but at distance 10 in the 90-degree direction.

References

Oden, N.L. and Sokal, R.R. 1986. Directional autocorrelation: an extension of spatial correlograms to two dimensions. Systematic Zoology 35: 608-617. doi:10.2307/2413120 @references Humston, R., Mortensen, D. and Bjornstad, O.N. 2005. Anthropogenic forcing on the spatial dynamics of an agricultural weed: the case of the common sunflower. Journal of Applied Ecology 42: 863-872. doi:10.1111/j.1365-2664.2005.01066.x

spline.correlog2D function