awaken: Simulate Awakening of Dormant Patterns

In dormancy: Detection and Analysis of Dormant Patterns in Data

Simulate Awakening of Dormant Patterns

Description

Simulates what would happen if a dormant pattern were to "awaken" - i.e., become active. This function allows exploration of potential future states and scenario analysis without waiting for actual pattern activation.

Usage

awaken(
  dormancy_result,
  pattern_id = 1,
  intensity = 1,
  n_sim = 100,
  return_data = FALSE,
  verbose = FALSE
)

Arguments

dormancy_result	An object of class "dormancy" from dormancy_detect.
pattern_id	Integer or "all". Which pattern(s) to awaken. Default is 1.
intensity	Numeric. Intensity of awakening, from 0 (dormant) to 1 (fully active). Default is 1.
n_sim	Integer. Number of simulation runs. Default is 100.
return_data	Logical. Whether to return simulated data. Default is FALSE.
verbose	Logical. Whether to print progress messages. Default is FALSE.

Details

Awakening simulation is valuable for:

• Scenario planning and stress testing

• Understanding potential system behaviors

• Preparing for pattern activation events

• Testing the robustness of current strategies

The simulation works by:

1. Identifying the dormant pattern's trigger conditions

2. Simulating data where those conditions are met

3. Applying the pattern's relationship to the simulated data

4. Measuring the resulting effects on the system

Value

A list containing:

• awakening_effects - Data frame describing the effects of awakening

• simulated_stats - Summary statistics from simulations

• cascade_effects - Effects on other patterns (if any)

• simulated_data - If return_data = TRUE, simulated datasets

Examples

set.seed(42)
n <- 500
x <- rnorm(n)
z <- sample(c(0, 1), n, replace = TRUE)
y <- ifelse(z == 1, 0.8 * x + rnorm(sum(z), 0, 0.3), rnorm(n))
data <- data.frame(x = x, y = y, z = factor(z))

result <- dormancy_detect(data, method = "conditional")
awakening <- awaken(result, pattern_id = 1, n_sim = 50)
print(awakening)

dormancy documentation built on March 16, 2026, 5:09 p.m.