| spatial_data {sparrpowR} | R Documentation |
Simulate random data for SRR function
Description
Generate random two-group data for a spatial relative risk 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
win |
Window in which to simulate the random data. An object of class "owin" or something acceptable to |
sim_total |
Integer, specifying the number of simulation iterations to perform. |
x_case |
Numeric value, or numeric vector, of x-coordinate(s) of case cluster(s). |
y_case |
Numeric value, or numeric vector, of y-coordinate(s) of case cluster(s). |
samp_case |
Character string specifying whether to randomize the case locations uniformly ( |
samp_control |
Character string specifying whether to randomize the control locations uniformly ( |
x_control |
Numeric value, or numeric vector, of x-coordinate(s) of case cluster(s). Ignored if |
y_control |
Numeric value, or numeric vector, of y-coordinate(s) of case cluster(s). Ignored if |
n_case |
Numeric value, or numeric vector, of the sample size for case locations in each cluster. |
n_control |
Numeric value, or numeric vector, of the sample size for control locations in each cluster. |
npc_control |
Optional. Numeric value of the number of clusters of control locations. Ignored if |
r_case |
Optional. Numeric value, or numeric vector, of radius (radii) of case cluster(s) in the units of |
r_control |
Optional. Numeric value, or numeric vector, of radius (radii) of control cluster(s) in the units of |
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 |
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 |
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 |
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 |
e_control |
Optional. A single non-negative number for the size of the expansion of the simulation window for generating parent points. Ignored if |
... |
Arguments passed to |
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 spatstat.random package to generate data.
If samp_case = "uniform" the case locations are randomly generated uniformly within a disc of radius r_case (or discs of radii r_case) centered at coordinates (x_case, y_case).
If samp_case = "MVN" the case locations are randomly generated assuming a multivariate normal distribution centered at coordinates (x_case, y_case) with a standard deviation of s_case.
If samp_case = "CSR" the case locations are randomly generated assuming complete spatial randomness (homogeneous Poisson process) within a disc of radius r_case (or discs of radii r_case) centered at coordinates (x_case, y_case) with lambda = n_case / area of disc.
If samp_case = "IPP" the case locations are randomly generated assuming an inhomogeneous Poisson process with a disc of radius r_case (or discs of radii r_case) centered at coordinates (x_case, y_case) with lambda = l_case, a function.
If samp_control = "uniform" the control locations are randomly generated uniformly within the window win.
If samp_control = "systematic" the control locations are randomly generated systematically within the window win consisting of a grid of equally-spaced points with a random common displacement.
If samp_control = "MVN" the control locations are randomly generated assuming a multivariate normal distribution centered at coordinates (x_control, y_control) with a standard deviation of s_control.
If samp_control = "CSR" the control locations are randomly generated assuming complete spatial randomness (homogeneous Poisson process) within the window win with a lambda = n_control / [resolution x resolution]. By default, the resolution is an integer value of 128 and can be specified using the resolution argument in the internally called risk function.
If samp_control = "IPP" the control locations are randomly generated assuming an inhomogeneous Poisson process within the window win with a lambda = l_control, a function.
If samp_control = "clustered" the control locations are randomly generated with a realization of the Neyman-Scott process within the window win with the intensity of the Poisson process cluster centres (kappa = l_control), the size of the expansion of the simulation window for generative parent points (e_control), and the radius (or radii) of the disc for each cluster (r_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.
See Also
runifdisc, disc, rpoispp, rsyst, or rNeymanScott for additional arguments for random point pattern generation.
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)