ripley: Ripley's K
In REAT: Regional Economic Analysis Toolbox

Description Usage Arguments Details Value Author(s) References See Also Examples

Analyzing point clustering with Ripley's K function

ripley(loc_df, loc_id, loc_lat, loc_lon, 
area, t.max, t.sep = 10, K.local = FALSE, 
ci.boot = FALSE, ci.alpha = 0.05, ciboot.samples = 100,
progmsg = FALSE, K.plot = TRUE, Kplot.func = "K",
plot.title = "Ripley's K", plotX = "t", 
plotY = paste(Kplot.func, "Observed vs. expected"), 
lcol.exp = "blue", lcol.emp = "red", lsize.exp = 1, 
ltype.exp = "solid", lsize.emp = 1, ltype.emp = "solid",
bg.col = "gray95", bgrid = TRUE, bgrid.col = "white", 
bgrid.size = 2, bgrid.type = "solid")

`loc_df`	A data frame containing the points
`loc_id`	Column containing the IDs of the points in the data frame `loc_df`
`loc_lat`	Column containing the latitudes of the points in the data frame `loc_df`
`loc_lon`	Column containing the longitudes of the points in the data frame `loc_df`
`area`	Total area of the regarded region
`t.max`	Maximum distance
`t.sep`	Number of distance intervals
`K.local`	Logical arguments that indicates whether local K values are computed or not
`ci.boot`	Logical arguments that indicates whether bootstrap confidence intervals are computed or not
`ci.alpha`	Significance level of the bootstrap confidence intervals
`ciboot.samples`	No. of bootstrap samples
`progmsg`	Logical argument: Printing progress messages or not
`K.plot`	Logical argument: Plot K function or not
`Kplot.func`	Which function has to be plotted? K function (`Kplot.func = "K"`), L function (`Kplot.func = "L"`) or H function (`Kplot.func = "H"`)
`plot.title`	If `K.plot = TRUE`: Plot title
`plotX`	If `K.plot = TRUE`: name of the X axis
`plotY`	If `K.plot = TRUE`: name of the Y axis
`lcol.exp`	If `K.plot = TRUE`: color of the line representing the expected values
`lcol.emp`	If `K.plot = TRUE`: color of the line representing the empirical values
`lsize.exp`	If `K.plot = TRUE`: size of the line representing the expected values
`lsize.emp`	If `K.plot = TRUE`: size of the line representing the empirical values
`ltype.exp`	If `K.plot = TRUE`: type of the line representing the expected values
`ltype.emp`	If `K.plot = TRUE`: type of the line representing the empirical values
`bg.col`	if `lc = TRUE` (plot of Lorenz curve), `bg.col` defines the background color of the plot (default: `"gray95"`)
`bgrid`	if `lc = TRUE` (plot of Lorenz curve), the logical argument `bgrid` defines if a grid is shown in the plot
`bgrid.col`	if `lc = TRUE` (plot of Lorenz curve) and `bgrid = TRUE` (background grid), `bgrid.col` defines the color of the background grid (default: "white")
`bgrid.size`	if `lc = TRUE` (plot of Lorenz curve) and `bgrid = TRUE` (background grid), `bgrid.size` defines the size of the background grid (default: 2)
`bgrid.type`	if `lc = TRUE` (plot of Lorenz curve) and `bgrid = TRUE` (background grid), `bgrid.type` defines the type of lines of the background grid (default: `"solid"`)

Calculating and plotting of the K function and its derivations (L function, H function) and, optionally, bootstrap confidence intervals.

The function returns a list containing:

`K`	A `data.frame` containing the K/L/H/t values
`K_local`	A `data.frame` containing the local K values (if stated)
`local_ci`	A `data.frame` containing the local confidence intervals (if stated)

Thomas Wieland

Kiskowski, M.A./Hancock, J. F./Kenworthy, A. (2009): “On the Use of Ripley's K-function and its Derivatives to Analyze Domain Size”. In: Biophysical Journal, 97, 4, p. 1095-1103.

Krider, R. E./Putler, R. S. (2013): “Which Birds of a Feather Flock Together? Clustering and Avoidance Patterns of Similar Retail Outlets”. In: Geographical Analysis, 45, 2, p. 123-149.

dist, dist.buf, dist.mat

## Not run: 
data(GoettingenHealth1)
# general practitioners, psychotherapists and pharmacies

area_goe <- 1753000000
# area of Landkreis Goettingen (sqm)
area_nom <- 1267000000
# area of Landkreis Northeim (sqm)
area_gn <- area_goe+area_nom
sqrt(area_gn/pi)

# this takes some seconds
ripley(GoettingenHealth1[GoettingenHealth1$type == "phys_gen",], 
"location", "lat", "lon", area = area_gn, t.max = 30000, t.sep = 300)

ripley(GoettingenHealth1[GoettingenHealth1$type == "pharm",], 
"location", "lat", "lon", area = area_gn, t.max = 30000, t.sep = 300)

ripley(GoettingenHealth1[GoettingenHealth1$type == "psych",], 
"location", "lat", "lon", area = area_gn, t.max = 30000, t.sep = 300)

## End(Not run)