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spatial_data.Rd
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/spatial_data.R
\name{spatial_data}
\alias{spatial_data}
\title{Simulate random data for SRR function}
\usage{
spatial_data(
win = spatstat.geom::unit.square(),
sim_total = 2,
x_case,
y_case,
samp_case = c("uniform", "MVN", "CSR", "IPP"),
samp_control = c("uniform", "systematic", "MVN", "CSR", "IPP", "clustered"),
x_control = NULL,
y_control = NULL,
n_case = NULL,
n_control = NULL,
npc_control = NULL,
r_case = NULL,
r_control = NULL,
s_case = NULL,
s_control = NULL,
l_case = NULL,
l_control = NULL,
e_control = NULL,
...
)
}
\arguments{
\item{win}{Window in which to simulate the random data. An object of class "owin" or something acceptable to \code{\link[spatstat.geom]{as.owin}}.}
\item{sim_total}{Integer, specifying the number of simulation iterations to perform.}
\item{x_case}{Numeric value, or numeric vector, of x-coordinate(s) of case cluster(s).}
\item{y_case}{Numeric value, or numeric vector, of y-coordinate(s) of case cluster(s).}
\item{samp_case}{Character string specifying whether to randomize the case locations uniformly (\code{samp_control = "uniform"}), multivariate normal (\code{samp_control = "MVN"}), with complete spatial randomness (\code{samp_control = "CSR"}), or using the inhomogeneous Poisson process (\code{samp_control = "IPP"}) around each case centroid.}
\item{samp_control}{Character string specifying whether to randomize the control locations uniformly (\code{samp_control = "uniform"}), systematically (\code{samp_control = "systematic"}), multivariate normal (\code{samp_control = "MVN"}), with complete spatial randomness (\code{samp_control = "CSR"}), using the inhomogeneous Poisson process (\code{samp_control = "IPP"}), or a realization of the Neyman-Scott cluster process (\code{samp_control = "clustered"}).}
\item{x_control}{Numeric value, or numeric vector, of x-coordinate(s) of case cluster(s). Ignored if \code{samp_control != "MVN"}.}
\item{y_control}{Numeric value, or numeric vector, of y-coordinate(s) of case cluster(s). Ignored if \code{samp_control != "MVN"}.}
\item{n_case}{Numeric value, or numeric vector, of the sample size for case locations in each cluster.}
\item{n_control}{Numeric value, or numeric vector, of the sample size for control locations in each cluster.}
\item{npc_control}{Optional. Numeric value of the number of clusters of control locations. Ignored if \code{samp_control != "clustered"}.}
\item{r_case}{Optional. Numeric value, or numeric vector, of radius (radii) of case cluster(s) in the units of \code{win}. Ignored if \code{samp_case = "MVN"}.}
\item{r_control}{Optional. Numeric value, or numeric vector, of radius (radii) of control cluster(s) in the units of \code{win}. Ignored if \code{samp_control != "clustered"}.}
\item{s_case}{Optional. Numeric value, or numeric vector, for the standard deviation(s) of the multivariate normal distribution for case locations in the units of \code{win}. Ignored if \code{samp_control != "MVN"}.}
\item{s_control}{Optional. Numeric value, or numeric vector, for the standard deviation(s) of the multivariate normal distribution for control locations in the units of \code{win}. Ignored if \code{samp_control != "MVN"}.}
\item{l_case}{Optional. A single positive number, a vector of positive numbers, a function(x,y, ...), or a pixel image. Intensity of the Poisson process for case clusters. Ignored if \code{samp_control != "IPP"}.}
\item{l_control}{Optional. A single positive number, a vector of positive numbers, a function(x,y, ...), or a pixel image. Intensity of the Poisson process for control clusters. Ignored if \code{samp_control = "uniform"}, \code{samp_control = "systematic"}, \code{samp_control = "MVN"}, or \code{samp_control = "CSR"}.}
\item{e_control}{Optional. A single non-negative number for the size of the expansion of the simulation window for generating parent points. Ignored if \code{samp_control != "clustered"}.}
\item{...}{Arguments passed to \code{\link[spatstat.random]{runifdisc}}, \code{\link[spatstat.geom]{disc}}, \code{\link[spatstat.random]{rpoispp}}, \code{\link[spatstat.geom]{rsyst}}, or \code{\link[spatstat.random]{rNeymanScott}} depending on \code{samp_control} or \code{samp_control}.}
}
\value{
An object of class "ppplist". This is a list of marked point patterns that have a single mark with two levels: case and control.
}
\description{
Generate random two-group data for a spatial relative risk function.
}
\details{
This function generates random data for a spatial relative risk function (nonparametric estimate of relative risk by kernel smoothing) using various random point pattern generators from the \code{\link{spatstat.random}} package to generate data.
If \code{samp_case = "uniform"} the case locations are randomly generated uniformly within a disc of radius \code{r_case} (or discs of radii \code{r_case}) centered at coordinates (\code{x_case}, \code{y_case}).
If \code{samp_case = "MVN"} the case locations are randomly generated assuming a multivariate normal distribution centered at coordinates (\code{x_case}, \code{y_case}) with a standard deviation of \code{s_case}.
If \code{samp_case = "CSR"} the case locations are randomly generated assuming complete spatial randomness (homogeneous Poisson process) within a disc of radius \code{r_case} (or discs of radii \code{r_case}) centered at coordinates (\code{x_case}, \code{y_case}) with \code{lambda = n_case / area of disc}.
If \code{samp_case = "IPP"} the case locations are randomly generated assuming an inhomogeneous Poisson process with a disc of radius \code{r_case} (or discs of radii \code{r_case}) centered at coordinates (\code{x_case}, \code{y_case}) with \code{lambda = l_case}, a function.
If \code{samp_control = "uniform"} the control locations are randomly generated uniformly within the window \code{win}.
If \code{samp_control = "systematic"} the control locations are randomly generated systematically within the window \code{win} consisting of a grid of equally-spaced points with a random common displacement.
If \code{samp_control = "MVN"} the control locations are randomly generated assuming a multivariate normal distribution centered at coordinates (\code{x_control}, \code{y_control}) with a standard deviation of \code{s_control}.
If \code{samp_control = "CSR"} the control locations are randomly generated assuming complete spatial randomness (homogeneous Poisson process) within the window \code{win} with a \code{lambda = n_control / [resolution x resolution]}. By default, the resolution is an integer value of 128 and can be specified using the \code{resolution} argument in the internally called \code{\link[sparr]{risk}} function.
If \code{samp_control = "IPP"} the control locations are randomly generated assuming an inhomogeneous Poisson process within the window \code{win} with a \code{lambda = l_control}, a function.
If \code{samp_control = "clustered"} the control locations are randomly generated with a realization of the Neyman-Scott process within the window \code{win} with the intensity of the Poisson process cluster centres (\code{kappa = l_control}), the size of the expansion of the simulation window for generative parent points (\code{e_control}), and the radius (or radii) of the disc for each cluster (\code{r_control}).
}
\examples{
spatial_data(x_case = c(0.25, 0.5, 0.75),
y_case = c(0.75, 0.25, 0.75),
samp_case = "MVN",
samp_control = "MVN",
x_control = c(0.25, 0.5, 0.75),
y_control = c(0.75, 0.25, 0.75),
n_case = 100,
n_control = c(100,500,300),
s_case = c(0.05,0.01,0.05),
s_control = 0.05,
verbose = FALSE)
}
\seealso{
\code{\link[spatstat.random]{runifdisc}}, \code{\link[spatstat.geom]{disc}}, \code{\link[spatstat.random]{rpoispp}}, \code{\link[spatstat.geom]{rsyst}}, or \code{\link[spatstat.random]{rNeymanScott}} for additional arguments for random point pattern generation.
}