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Identify Trigger Conditions for Dormant Patterns

Source: R/dormancy_trigger.R
dormancy_trigger.Rd

Analyzes detected dormant patterns to identify the specific conditions under which they would activate. This function goes beyond detection to characterize the precise trigger mechanisms and their sensitivity.

Usage

dormancy_trigger(
  dormancy_result,
  sensitivity = 0.5,
  n_bootstrap = 100,
  verbose = FALSE
)

Arguments

dormancy_result

An object of class "dormancy" from dormancy_detect.

sensitivity

Numeric. The sensitivity level for trigger detection, ranging from 0 (low sensitivity, only major triggers) to 1 (high sensitivity, minor triggers included). Default is 0.5.

n_bootstrap

Integer. Number of bootstrap samples for confidence intervals. Default is 100.

verbose

Logical. Whether to print progress messages. Default is FALSE.

Value

A list containing:

  • triggers - A data frame with trigger details: pattern_id, trigger_variable, trigger_type, threshold_value, sensitivity_score, confidence_lower, confidence_upper

  • trigger_map - A matrix showing trigger relationships

  • recommendations - Character vector of actionable insights

Details

Trigger identification is crucial for risk management and early warning systems. A dormant pattern might be triggered by:

  • Threshold triggers: When a variable crosses a specific value

  • Region triggers: When observations fall within specific data regions

  • Categorical triggers: When a categorical condition is met

  • Compound triggers: When multiple conditions align

  • Temporal triggers: When time-dependent patterns emerge

The function uses bootstrap resampling to provide confidence intervals around trigger estimates, ensuring robust identification even with limited data.

See also

dormancy_detect, dormancy_risk

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(n, 0, 0.3), rnorm(n))
data <- data.frame(x = x, y = y, z = factor(z))

result <- dormancy_detect(data, method = "conditional")
triggers <- dormancy_trigger(result)
#> Warning: No dormant patterns detected. Run dormancy_detect first.
print(triggers)
#> $triggers
#> data frame with 0 columns and 0 rows
#> 
#> $trigger_map
#>      [,1]
#> [1,]   NA
#> 
#> $recommendations
#> [1] "No dormant patterns to analyze."
#>