gemseo / uncertainty / statistics / tolerance_interval

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normal module

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

class gemseo.uncertainty.statistics.tolerance_interval.normal.NormalToleranceInterval(size, mean, std)[source]

Bases: ToleranceInterval

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

The formulae come from the R library tolerance [1].

Intervals*, Journal of Statistical Software, 36(5), 2010

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

  • mean (float) – The estimation of the mean of the normal distribution.

  • std (float) – The estimation of the standard deviation of the normal distribution.

class Bounds(lower, upper)

Bases: NamedTuple

The component-wise bounds of a vector.

Create new instance of Bounds(lower, upper)

Parameters:
  • lower (NDArray[float]) –

  • upper (NDArray[float]) –

count(value, /)

Return number of occurrences of value.

index(value, start=0, stop=9223372036854775807, /)

Return first index of value.

Raises ValueError if the value is not present.

lower: NDArray[float]

Alias for field number 0

upper: NDArray[float]

Alias for field number 1

class ToleranceIntervalSide(value)

Bases: LowercaseStrEnum

The side of the tolerance interval.

BOTH = 'both'
LOWER = 'lower'
UPPER = 'upper'
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 (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:

Bounds