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
)
#> Outcome: 0 (1/2)
#> Outcome: 1 (2/2)