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  2. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    The log-normal distribution has also been associated with other names, such as McAlister, Gibrat and Cobb–Douglas. [4] A log-normal process is the statistical realization of the multiplicative product of many independent random variables, each of which is positive.

  3. File:Lognormal distribution PDF.svg - Wikipedia

    en.wikipedia.org/wiki/File:Lognormal...

    Lognormal distribution PDF.png licensed with Cc-by-sa-3.0-migrated, GFDL 2005-05-03T04:48:16Z PAR 1300x975 (192660 Bytes) Probability density function for the Log-normal distribution; Uploaded with derivativeFX

  4. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    The simplest case of a normal distribution is known as the standard normal distribution or unit normal distribution. This is a special case when μ = 0 {\textstyle \mu =0} and σ 2 = 1 {\textstyle \sigma ^{2}=1} , and it is described by this probability density function (or density): φ ( z ) = e − z 2 2 2 π . {\displaystyle \varphi (z ...

  5. Log probability - Wikipedia

    en.wikipedia.org/wiki/Log_probability

    In probability theory and computer science, a log probability is simply a logarithm of a probability. [1] The use of log probabilities means representing probabilities on a logarithmic scale ( − ∞ , 0 ] {\displaystyle (-\infty ,0]} , instead of the standard [ 0 , 1 ] {\displaystyle [0,1]} unit interval .

  6. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The log-logistic distribution; The log-metalog distribution, which is highly shape-flexile, has simple closed forms, can be parameterized with data using linear least squares, and subsumes the log-logistic distribution as a special case. The log-normal distribution, describing variables which can be modelled as the product of many small ...

  7. Logarithmically concave function - Wikipedia

    en.wikipedia.org/wiki/Logarithmically_concave...

    Every distribution with log-concave density is a maximum entropy probability distribution with specified mean μ and Deviation risk measure D. [2] As it happens, many common probability distributions are log-concave. Some examples: [3] the normal distribution and multivariate normal distributions, the exponential distribution,

  8. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    Figure 2: The probability density function (pdf) of the normal distribution, also called Gaussian or "bell curve", the most important absolutely continuous random distribution. As notated on the figure, the probabilities of intervals of values correspond to the area under the curve.

  9. File:PDF-log normal distributions.svg - Wikipedia

    en.wikipedia.org/wiki/File:PDF-log_normal...

    The following other wikis use this file: Usage on bg.wikipedia.org Логаритъм; Usage on en.wikibooks.org The science of finance/Probabilities and evaluation of risks