Summarize Second Moment Method results.

Summarizes the propagated moments and reports the percentiles implied by a normal approximation.

Usage

# S3 method for class 'smm'
summary(object, conf_level = 0.95, ...)

Arguments

object

An object of class "smm".

conf_level

Unused placeholder retained for symmetry; percentiles are fixed at P5/P50/P95.

...

Additional arguments (not used).

Value

An object of class "summary.smm", a list with components:

total_mean, total_variance, total_sd

Propagated moments. Note the canonical names, which match those used by summary.mcs(); the smm object itself carries total_var and total_std.

cv

Coefficient of variation. NA when the mean is zero.

percentiles

Named numeric vector of the P5, P50 and P95 percentiles implied by the normal approximation.

Details

The Second Moment Method constrains only the first two moments of the total, so the percentiles reported here are those of the normal distribution with that mean and variance. This is the maximum-entropy distribution consistent with what SMM computes, but it is an approximation: durations and costs are non-negative while the normal is not, so the lower percentiles are unreliable when total_mean is less than roughly three standard deviations. Use mcs() when the shape of the distribution matters.

Examples

result <- smm(c(10, 15, 20), c(4, 9, 16))
summary(result)
#> Second Moment Method Summary
#> ------------------------------
#> Total Mean:  45 
#> Total Variance:  29 
#> Total Standard Deviation:  5.385165 
#> Coefficient of Variation:  0.1197 
#> 
#> Percentiles (normal approximation):
#>       5%      50%      95% 
#> 36.14219 45.00000 53.85781