Available sampling constraints

TruncateStd(nσ::Number)

A constraint indicating that the distribution furnishing an uncertain value should be truncated at the mean ± nσ (n standard deviations).

Notes

• Beware when you apply the TruncateStd constraint to a (usually a numeric) population with a small value range. With nσ small, you might end up with a population mean between the actual values, so that the range [mean(pop) - nσ*std(pop), mean(pop) + nσ*std(pop)] returns nothing.

TruncateMinimum(min::Number)

A constraint indicating that the distribution furnishing an uncertain value should be truncated below at some specified minimum value.

TruncateMaximum(max::Number)

A constraint indicating that the distribution furnishing an uncertain value should be truncated above at some specified maximum value.

TruncateRange(min::Number, max::Number)

A constraint indicating that the distribution furnishing an uncertain value should be truncated at some range [min, max].

TruncateLowerQuantile(lower_quantile::Float64)

A constraint indicating that the distribution furnishing an uncertain value should be truncated below at some quantile.

TruncateUpperQuantile(upper_quantile::Float64)

A constraint indicating that the distribution furnishing an uncertain value should be truncated above at some quantile.

TruncateQuantiles(lower_quantile::Float64, upper_quantile::Float64)

A constraint indicating that the distribution furnishing an uncertain value should be truncated at some quantile quantile (lower_quantile, upper_quantile).