SpatialML (version 1.8.2)

random.test.data: Random Data Generator

Description

Generates a synthetic data set composed of one dependent variable, a number of independent variables drawn from Uniform(0, 1), and optionally the X and Y coordinates of a regular nrows x ncols grid. Useful for examples, unit testing and small simulation studies.

Usage

random.test.data(nrows = 10, ncols = 10, vars.no = 3,
                 dep.var.dis = c("normal", "poisson"),
                 xycoords = TRUE)

Value

A data frame with nrows * ncols rows containing one column dep, vars.no - 1 columns named X1, X2, ... and, when xycoords = TRUE, two extra columns X and Y.

Arguments

nrows

integer; number of rows of the regular grid. Default 10.

ncols

integer; number of columns of the regular grid. Default 10.

vars.no

integer; total number of model variables (1 dependent plus vars.no - 1 independent). Must be at least 2.

dep.var.dis

distribution of the dependent variable. One of "normal" (default, drawn from rnorm()) or "poisson" (drawn from rpois() with lambda = 7).

xycoords

logical; if TRUE (default) two columns X and Y containing the grid coordinates are appended.

Author

Stamatis Kalogirou

Details

The function is mostly intended to provide reproducible toy data for the package examples. The independent variables are named X1, X2, ..., X(vars.no - 1).

For reproducible results call set.seed() before random.test.data().

Examples

set.seed(1)
RDF <- random.test.data(12, 12, 3)
head(RDF)