cont2cat | R Documentation |
Create break points, compute strata proportions, and stratify numerical variable(s) to create categorical variable(s).
cont2cat(x, breaks, integer = FALSE) breakPoints(x, n, type = "area", prop = FALSE) stratify(x, n, type = "area", integer = FALSE)
x |
Vector, data frame or matrix with data on the numerical variable(s) to be categorized/stratified. |
breaks |
Vector or list containing the lower and upper limits that should be used to break the numerical variable(s) into categories. See ‘Details’ for more information. |
integer |
Logical value indicating if the categorical variable(s) should be returned as
|
n |
Integer value indicating the number of categories/strata that should be created. |
type |
Character value indicating the type of categories/strata that should be used, with
options |
prop |
Logical value indicating if the strata proportions should be returned? Defaults to
|
Argument breaks
must be a vector if x
is a vector, but a list if x
is a data frame or
matrix. Using a list allows breaking each column of x
into different number of categories.
A vector, data frame, or matrix, depending on the class of x
.
The SpatialTools package, provider of tools for spatial data analysis in R, is required for
breakPoints()
and stratify()
to work. The development version of
the SpatialTools package is available on https://github.com/jfrench/SpatialTools while its
old versions are available on the CRAN archive at
https://cran.r-project.org/src/contrib/Archive/SpatialTools/.
The spsann package, provider of methods for the optimization of sample configurations using
spatial simulated annealing in R, requires breakPoints()
,
cont2cat()
and stratify()
for some of its functions to work. The
development version of the spsann package is available on
https://github.com/Laboratorio-de-Pedometria/spsann-package.
Alessandro Samuel-Rosa alessandrosamuelrosa@gmail.com
B. Minasny and A. B. McBratney. A conditioned Latin hypercube method for sampling in the presence of ancillary information. Computers & Geosciences, vol. 32, no. 9, pp. 1378–1388, Nov. 2006, doi: 10.1016/j.cageo.2005.12.009.
T. Hengl, D. G. Rossiter, and A. Stein. Soil sampling strategies for spatial prediction by correlation with auxiliary maps. Australian Journal of Soil Research, vol. 41, no. 8, pp. 1403–1422, 2003, doi: 10.1071/SR03005.
if (require(SpatialTools)) { ## Compute the break points of marginal strata x <- data.frame(x = round(rnorm(10), 1), y = round(rlnorm(10), 1)) x <- breakPoints(x = x, n = 4, type = "area", prop = TRUE) ## Convert numerical data into categorical data # Matrix x <- y <- c(1:10) x <- cbind(x, y) breaks <- list(c(1, 2, 4, 8, 10), c(1, 5, 10)) y <- cont2cat(x, breaks) # Data frame x <- y <- c(1:10) x <- data.frame(x, y) breaks <- list(c(1, 2, 4, 8, 10), c(1, 5, 10)) y <- cont2cat(x, breaks, integer = TRUE) # Vector x <- c(1:10) breaks <- c(1, 2, 4, 8, 10) y <- cont2cat(x, breaks, integer = TRUE) ## Stratification x <- data.frame(x = round(rlnorm(10), 1), y = round(rnorm(10), 1)) x <- stratify(x = x, n = 4, type = "area", integer = TRUE) x }
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.