Home ยป Technology ยป ???? Weibull Distribution – Definition and Explanations

???? Weibull Distribution – Definition and Explanations

2023-06-22 03:38:13

Introduction

Weibull

Scale parameters (actual)
form (real) Support Probability density (In probability theory or in statistics, a probability density isโ€ฆ) (mass function) Distribution function (In probability theory or in statistics, the distribution function of a โ€ฆ) Median expectation (The term median, from the Latin medius, which is in the middle, has several acceptances inโ€ฆ) (center) Mode if k > 1 Variance ( In statistics and in probability, variance In thermodynamics, variance ) Asymmetry (Asymmetry is the absence of symmetry, or its inverse. In nature, crabsโ€ฆ) (statistics) Kurtosis
(non-normalized) see text Entropy (In thermodynamics, entropy is a state function introduced in 1865 by Rudolf Clausiusโ€ฆ) Generating function (In mathematics, the generating function of the sequence (an) is the formal series defined by) times edit

In probability theory (Probability theory is the mathematical study of phenomenaโ€ฆ), Weibullโ€™s law, named following Waloddi Weibull, is a law of probability (In probability theory and in statistics, a law of probability describedโ€ฆ) continues.

Characteristic functions

With two parameters its density (The density or relative density of a body is the ratio of its density to theโ€ฆ) probability (The probability (from the Latin probabilitas) is an assessment of the probable character of aโ€ฆ ) East :

where k > 0 is the shape parameter and ฮป > 0 the scale parameter of the distribution.

Its distribution function is defined by:

where, once more, x > 0.

With three parameters (generalized) its probability density is:

For x โ‰ฅ ฮธ and f(x; k, ฮป, ฮธ) = 0 for xk > 0 is the shape parameter, ฮป > 0 is the scale parameter and ฮธ is the location parameter of the distribution.

Its distribution function for the 3-parameter Weibull distribution is defined by:

Pour x โ‰ฅ ฮธ, et F(x; k, ฮป, ฮธ) = 0 pour x

The coefficient (In mathematics a coefficient is a multiplicative factor which depends on a certainโ€ฆ) of asymmetry (skewness) is given by:

Kurtosis is given by:

The failure rate h is given by:

Convenient use

General

The expression Weibullโ€™s law in fact covers a whole family of laws, some of them appearing in physics (Physics (from the Greek ฯ†ฯ…ฯƒฮนฯ‚, nature) is etymologically theโ€ฆ) as a consequence of certain hypotheses. This is, in particular, the case of the exponential law (An exponential law corresponds to the following model:) (k = 1) and of Rayleighโ€™s law (In probability and in statistics, Rayleighโ€™s law is a law of probability toโ€ฆ) (k = 2) material (Matter is the substance that makes up any body having a tangible reality. Itsโ€ฆ) of stochastic processes.

These laws above all constitute particularly useful approximations in various techniques, whereas it would be very difficult and without great interest to justify a particular form of law. A distribution with positive values โ€‹โ€‹(or, more generally but less frequently, with values โ€‹โ€‹greater than a given value) almost always looks the same. It starts from a frequency (In physics, frequency generally designates the measurement of the number of times aโ€ฆ) of zero appearance, increases to a maximum and decreases more slowly. It is then possible to find in the Weibull family a law which does not deviate too much from the data (In information technology (IT), a datum is an elementary description, oftenโ€ฆ) available by calculating and from the observed mean and variance.

Special application

The Weibull distribution (In probability theory, the Weibull distribution, named following Waloddi Weibull,โ€ฆ) is often used in the field of lifespan analysis (Life is the given name:) , thanks to its flexibility: as said previously, it makes it possible to represent at least approximately an infinity of probability distributions.

If the failure rate decreases over time (Time is a concept developed by human beings to understandโ€ฆ) then, k . If the failure rate is constant over time then k = 1. If the failure rate increases over time then k > 1. Understanding the failure rate can provide an indication (An indication (from the Latin indicare: to indicate ) is advice or a recommendation, writtenโ€ฆ) regarding the cause of failures.

A decreasing breakdown rate comes under โ€œinfant mortalityโ€. Thus, the defective elements fail quickly, and the failure rate decreases over time, when the fragile elements leave the population. A constant failure rate suggests that the failures are related to a stationary cause. An increasing failure rate suggests โ€œwear or a reliability problem (A system is reliable when the probability of fulfilling its mission over a period of timeโ€ฆ)โ€: the elements have more and more chances of breaking down when the time spent.

It is said that the yield curve (In finance, the expression yield curve designates the graphical or mathematical representation inโ€ฆ) of breakdown is in the shape of a bathtub. Depending on the device, hip bath or swimming pool. Manufacturers and distributors have every interest in mastering this information by type of product in order to adapt:

warranty periods (free or paid) maintenance schedule (see MTBF) Laws of probability Discrete laws with finite support Bernoulliโ€™s law (In mathematics, Bernoulliโ€™s distribution or Bernoulliโ€™s law, named following โ€ฆ) โ€ข Discrete uniform law โ€ข Binomial law (In mathematics, a binomial law with parameters n and p is a law of probabilityโ€ฆ) โ€ข Hypergeometric law (A hypergeometric law with parameters n, p and A corresponds to the following model:) โ€ข Law of Benford (Benfordโ€™s law, also called the law of abnormal numbers, is notโ€ฆ) Discrete laws with countable support Geometric law (The geometric law is a law of probability appearing in manyโ€ฆ) โ€ข Law of Poisson (In probability theory and in statistics, the Poisson distribution is a distribution ofโ€ฆ) โ€ข Negative binomial distribution (In probability and in statistics, the negative binomial distribution is a distribution ofโ€ฆ) โ€ข Logarithmic distribution Continuous distributions with compact support Uniform continuous law (In probability theory and in statistics, the uniform continuous law is aโ€ฆ) โ€ข Triangular law โ€ข Beta law (In probability theory and in statistics, the beta law is a family of. ..) Continuous laws with semi-infinite support Exponential law (The exponential function is one of the most important applications in analysis, or moreโ€ฆ) โ€ข Gamma law โ€ข ฯ‡ยฒ law โ€ข Fisherโ€™s law (In the Theory of probabilities and in Statistics, Fisherโ€™s law or even โ€ฆ) โ€ข Law of Weibull โ€ข Rayleighโ€™s law โ€ข Riceโ€™s law (In statistics and probability theory, Riceโ€™s law is a statistical lawโ€ฆ) โ€ข Erlangโ€™s law โ€ข Lรฉvyโ€™s law โ€ข Inverse-gamma law โ€ข Log-normal law Continuous laws at infinite support (The word โ€œinfinityโ€ (-e, -s; from the Latin finitus,โ€ฆ) Normal law (In probability, we say that a real random variable X follows a normal law (orโ€ฆ) โ€ข Law asymmetrical normal โ€ข Cauchyโ€™s law โ€ข Laplaceโ€™s law (See also (in electromagnetism) Laplaceโ€™s force.) โ€ข Logistic law (Logistics is the activity which aims to manage the physical flows of aโ€ฆ) โ€ข Law (Studentโ€™s law is a law of probability, involving the quotient between aโ€ฆ) โ€ข Stable law โ€ข Gumbelโ€™s law
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