calc_sdd {aspace} | R Documentation |
The dispersion of a set of points on a Cartesian plane can be described using the Standard Distance Deviation (SDD) or Standard Distance. For the purpose of geographic visualization, the SDD is typically portrayed as a circle with radius SDD centered on the mean center of a set of point observations. The orthogonal dispersion of a set of points can also be described using the standard deviation of the x- and y-coordinates of a set of point observations. The standard deviation of x- and y-coordinates can be geographically visualized using a box, with the edges set, respectively, to the standard deviation of the x- and y-coordinates.
calc_sdd(id = 1, filename = "SDD_Output.txt", centre.xy = centre, calccentre = TRUE, useWMC = FALSE, weightpoints = FALSE, weights = wts, destmat = activities, verbose = FALSE, plot = TRUE, plothv = TRUE, plotdest = TRUE, plotcenter = TRUE, box = TRUE)
id |
A unique integer to identify the shape |
filename |
A string indicating the ASCII textfile where shape coordinates will be written |
centre.xy |
A vector of length 2, containing the x- and y-coordinates of the SDD centroid |
calccentre |
Boolean: Set to TRUE if the mean center is to be calculated |
useWMC |
Boolean: Set to TRUE if the mean center is to be computed with weighted coordinates |
weightpoints |
Boolean: Set to TRUE if the point observations are to be weighted |
weights |
Weights applied to point observations |
destmat |
A 2-column matrix or data frame containing point coordinates |
verbose |
Boolean: Set to TRUE if extensive feedback is desired on the standard output |
plot |
Boolean: Set to TRUE if the SDD is to be plotted |
plothv |
Boolean: Set to TRUE if the orthogonal N-S, E-W axes are to be plotted through the center |
plotdest |
Boolean: Set to TRUE if the point observations are to be plotted |
plotcenter |
Boolean: Set to TRUE if the mean center is to be plotted |
box |
Boolean: Set to TRUE if the standard deviation of the x- and y-coordinates are to be plotted as a box |
This function is most powerful when used repetitively within a loop to compute the SDD for subsets of points stored in a large table.
The result is a list of terms:
id |
Identifier for the SDD shape - it should be unique |
calccentre |
True if mean centre is computed |
Orig.x |
Original x-coordinate of center before mean center calculation |
Orig.y |
Original y-coordinate of center before mean center calculation |
CENTRE.x |
Actual, used x-coordinate of centre |
CENTRE.y |
Actual, used y-coordinate of centre |
SD.x |
Standard deviation of the x-coordinates |
SD.y |
Standard deviation of the y-coordinates |
SDD.radius |
SDD value, radius of the SDD |
Box.area |
Area of the box formed by the standard deviation of the x- and y-coordinates |
SDD.area |
Area of the SDD circle |
useWMC |
Boolean: TRUE if the weighted mean center is used |
WeightPoints |
Boolean: TRUE if point observations are weighted |
This function can be used on its own (once) or repetitively in a loop to process grouped point data stored in a larger table. When used repetitively, be sure to increment the id parameter to ensure that each SDD has a unique identifier. The output ASCII coordinate file can be further processed using the makeshapes function to generate an ESRI Shapefile for SDD polygons.
Tarmo K. Remmel, Ron Buliung
ellipse3
, calc_mcp
,
calc_sde
, makeshapes
calc_sdd(id = 1, filename = "SDD_Output.txt", centre.xy = centre, calccentre = TRUE, useWMC = FALSE, weightpoints = FALSE, destmat = activities, verbose = FALSE, plot = TRUE, plothv = TRUE, plotdest = TRUE, plotcenter = TRUE, box = TRUE)