gemseo / uncertainty / statistics / tolerance_interval

# lognormal module¶

Computation of tolerance intervals from a data-fitted log-normal distribution.

class gemseo.uncertainty.statistics.tolerance_interval.lognormal.LogNormalToleranceInterval(size, mean, std, location)[source]

Computation of tolerance intervals from a data-fitted log-normal 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

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

• mean (float) – The estimation of the mean of the natural logarithm of a log-normal distributed random variable.

• std (float) – The estimation of the standard deviation of the natural logarithm of a log-normal distributed random variable.

• location (float) – The estimation of the location of the log-normal distributed.

Return type

None

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

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
docstring_processor(parent_doc: , child_func: Callable) None: Callable[[Optional[str], Callable], str] = <docstring_inheritance.processors.google.GoogleDocstringProcessor object>
Parameters
• parent_doc (Optional[str]) –

• child_func (Callable) –

Return type

None