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]

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

The formulae come from the R library tolerance _.

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)

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.

• 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]

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

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

The formulae come from the R library tolerance _.

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)

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.

• 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]