Evaluate Control Chart Rules — spm.rules • fdars

Applies Western Electric or Nelson run rules to a sequence of control chart values. Identifies patterns that indicate non-random behavior (e.g., runs, trends, points beyond control limits).

Usage

spm.rules(values, center, sigma, rule.set = c("western.electric", "nelson"))

Arguments

values: Numeric vector of chart values (in time order).
center: Center line value (e.g., process mean).
sigma: Standard deviation (for zone boundaries at 1, 2, 3 sigma).
rule.set: Which rule set to apply: "western.electric" (4 rules) or "nelson" (8 rules).

Value

An object of class spm.rules with components:

rules: Character vector of violated rule names
indices: List of integer vectors; each gives the observation indices (1-indexed) involved in that violation
values: The input values
center: The center line
sigma: The standard deviation
rule.set: The rule set used

Examples

# \donttest{
set.seed(1)
values <- c(rnorm(20), rnorm(5, mean = 3))
result <- spm.rules(values, center = 0, sigma = 1,
                    rule.set = "western.electric")
result
#> SPM Control Chart Rule Evaluation
#>   Rule set: western.electric 
#>   Observations: 25 
#>   Center: 0 
#>   Sigma: 1 
#>   Violations found: 11 
#>     WE1: indices [21]
#>     WE1: indices [22]
#>     WE1: indices [23]
#>     WE1: indices [25]
#>     WE2: indices [21, 22]
#>     WE2: indices [21, 22, 23]
#>     WE2: indices [22, 23]
#>     WE2: indices [23, 25]
#>     WE3: indices [21, 22, 23, 24]
#>     WE3: indices [21, 22, 23, 24, 25]
#>     WE4: indices [18, 19, 20, 21, 22, 23, 24, 25]
# }