simulatePP {funkycells}

Simulate a Point Process

Description

This function simulates a point pattern with optional clustering (visible and invisible). Multiple outcomes, units, and replicates are possible, e.g. a 3 stage disease (outcomes) over 20 people (units) with 3 images each (replicates).

Usage

simulatePP(
  agentVarData = data.frame(outcome = c(0, 1, 2), A = c(0, 0, 0), B = c(1/100, 1/500,
    1/500), C = c(1/500, 1/250, 1/100), D = c(1/100, 1/100, 1/100), E = c(1/500, 1/500,
    1/500), F = c(1/250, 1/250, 1/250)),
  agentKappaData = data.frame(agent = c("A", "B", "C", "D", "E", "F"), clusterAgent =
    c(NA, "A", "B", "C", NA, "A"), kappa = c(20, 5, 4, 2, 15, 5)),
  unitsPerOutcome = 20,
  replicatesPerUnit = 5,
  silent = FALSE
)

Arguments

agentVarData

(Optional) Data.frame describing variances with each agent type.

The data.frame has a outcome column and a named column for each agent type. Currently, these names are mandatory.

agentKappaData

(Optional) Data.frame describing agent interactions.

The data.frame has a agent column giving agent names (matching agentVarData), a clusterAgent column indicating which agent the agent clusters (put NA if the agent doesn't cluster or clusters a hidden agent / self-clusters), and a kappa column directing the number of agents of per replicate.

unitsPerOutcome

(Optional) Numeric indicating the number of units per outcome.

replicatesPerUnit

(Optional) Numeric indicating the number of replicates, or repeated measures, per unit.

silent

(Optional) Boolean indicating if progress output should be printed.

Value

Data.frame containing each point the defined patterns.

The data.frame has columns for outcome, x coordinate, y coordinate, agent type, unit, and replicate id.

Examples

data <- simulatePP(
  agentVarData = data.frame(
    "outcome" = c(0, 1),
    "A" = c(0, 0),
    "B" = c(1 / 100, 1 / 500),
    "C" = c(1 / 500, 1 / 250),
    "D" = c(1 / 100, 1 / 100),
    "E" = c(1 / 500, 1 / 500)
  ),
  agentKappaData = data.frame(
    "agent" = c("A", "B", "C", "D", "E"),
    "clusterAgent" = c(NA, "A", "B", "C", NA),
    "kappa" = c(10, 3, 2, 1, 8)
  ),
  unitsPerOutcome = 4,
  replicatesPerUnit = 1
)