gemseo / uncertainty / statistics / tolerance_interval

weibull module

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

Classes:

WeibullMinToleranceInterval(size, scale, …)

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

WeibullToleranceInterval(size, scale, shape, …)

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

class gemseo.uncertainty.statistics.tolerance_interval.weibull.WeibullMinToleranceInterval(size, scale, shape, location)[source]

Bases: gemseo.uncertainty.statistics.tolerance_interval.weibull.WeibullToleranceInterval

Computation of tolerance intervals from a data-fitted Weibull 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.

  • scale (float) – The estimation of the scale of the Weibull distribution.

  • shape (float) – The estimation of the shape of the Weibull distribution.

  • location (float) – The estimation of the location of the Weibull distribution.

Return type

None

Methods:

compute(coverage[, confidence, side])

Compute a tolerance interval.

compute(coverage, confidence=0.95, side=<ToleranceIntervalSide.BOTH: 3>)

Compute a tolerance interval.

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

  • confidence (float) – A level of confidence in [0,1].

  • 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 \([c, d]\).

Returns

The tolerance bounds.

Return type

Tuple[numpy.ndarray, numpy.ndarray]

class gemseo.uncertainty.statistics.tolerance_interval.weibull.WeibullToleranceInterval(size, scale, shape, location)[source]

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

Computation of tolerance intervals from a data-fitted Weibull 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.

  • scale (float) – The estimation of the scale of the Weibull distribution.

  • shape (float) – The estimation of the shape of the Weibull distribution.

  • location (float) – The estimation of the location of the Weibull distribution.

Return type

None

Methods:

compute(coverage[, confidence, side])

Compute a tolerance interval.

compute(coverage, confidence=0.95, side=<ToleranceIntervalSide.BOTH: 3>)

Compute a tolerance interval.

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

  • confidence (float) – A level of confidence in [0,1].

  • 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 \([c, d]\).

Returns

The tolerance bounds.

Return type

Tuple[numpy.ndarray, numpy.ndarray]