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Download a pdf copy of this help file here |
Format: VoseWeibull(a, b, U)
Examples of the Weibull distribution are given below:
The Weibull distribution is often used to model the time until occurrence of an event where the probability of occurrence changes with time (the process has 'memory'), as opposed to the Exponential distribution where the probability of occurrence remains constant ('memoryless'). It has also been used to model variation in wind speed at a specific site. Example: Light bulbs.
The Weibull distribution becomes an exponential distribution when a = 1, i.e. Weibull(1, b) = Expon(b). The Weibull distribution is very close to the Normal distribution when b= 3.25. The Weibull distribution is named after the Swedish physicist Dr E. H. Wallodi Weibull (1887-1979) who used it to model the distribution of the breaking strengths of materials.
The WeibulAlt distribution determines a Weibull distribution defined by two percentiles.
VoseWeibull generates values from this distribution or calculates a percentile.
VoseWeibullObject constructs a distribution object for this distribution. Professional and Industrial editions only.
VoseWeibullProb returns the probability density or cumulative distribution function for this distribution. Professional and Industrial editions only.
VoseWeibullProb10 returns the log10 of the probability density or cumulative distribution function. Professional and Industrial editions only.
VoseWeibullFit generates values from this distribution fitted to data, or calculates a percentile from the fitted distribution. Professional and Industrial editions only.
VoseWeibullFitObject constructs a distribution object of this distribution fitted to data. Professional and Industrial editions only.
VoseWeibullFitP returns the parameters of this distribution fitted to data. Professional and Industrial editions only.
