normal module¶
Computation of tolerance intervals from a data-fitted normal distribution.
Classes:
|
Computation of tolerance intervals from a data-fitted normal distribution. |
- class gemseo.uncertainty.statistics.tolerance_interval.normal.NormalToleranceInterval(size, mean, std)[source]¶
Bases:
gemseo.uncertainty.statistics.tolerance_interval.distribution.ToleranceInterval
Computation of tolerance intervals from a data-fitted 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
Initialize self. See help(type(self)) for accurate signature.
- 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.
- 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]