gemseo / uncertainty / statistics / tolerance_interval

uniform module

Computation of tolerance intervals from a data-fitted uniform distribution.

Classes:

UniformToleranceInterval(size, minimum, maximum)

Computation of tolerance intervals from a data-fitted uniform distribution.

class gemseo.uncertainty.statistics.tolerance_interval.uniform.UniformToleranceInterval(size, minimum, maximum)[source]

Bases: gemseo.uncertainty.statistics.tolerance_interval.distribution.ToleranceInterval

Computation of tolerance intervals from a data-fitted uniform distribution.

The formulae come from the R library tolerance 1.

1

Derek S. Young, tolerance: An R Package for Estimating Tolerance Intervals, Journal of Statistical Software, 36(5), 2010

Initialize self. See help(type(self)) for accurate signature.

Parameters
  • size (int) – The number of samples.

  • minimum (float) – The estimation of the lower bound of the uniform distribution.

  • maximum (float) – The estimation of the upper bound of the uniform distribution.

Return type

None

Methods:

compute(coverage[, confidence, side])

Compute a tolerance interval.

compute(coverage, confidence=0.95, side=ToleranceIntervalSide.BOTH)

Compute a tolerance interval.

Parameters
  • coverage (float) – A minimum percentage of belonging to the TI.

  • confidence (float) –

    A level of confidence in [0,1].

    By default it is set to 0.95.

  • side (gemseo.uncertainty.statistics.tolerance_interval.distribution.ToleranceIntervalSide) –

    The type of the tolerance interval characterized by its sides of interest, either a lower-sided tolerance interval \([a, +\infty[\), an upper-sided tolerance interval \(]-\infty, b]\), or a two-sided tolerance interval \([c, d]\).

    By default it is set to BOTH.

Returns

The tolerance bounds.

Return type

Tuple[numpy.ndarray, numpy.ndarray]