spatial_data | R Documentation |

Generate random two-group data for a spatial relative risk function.

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, ... )

`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 |

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`

).

An object of class "ppplist". This is a list of marked point patterns that have a single mark with two levels: case and control.

`runifdisc`

, `disc`

, `rpoispp`

, `rsyst`

, or `rNeymanScott`

for additional arguments for random point pattern generation.

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)

sparrpowR documentation built on Feb. 16, 2023, 5:53 p.m.

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