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The file size distribution of publicly available audio and video data files follows a log-normal distribution over five orders of magnitude. [92] File sizes of 140 million files on personal computers running the Windows OS, collected in 1999. [93] [62] Sizes of text-based emails (1990s) and multimedia-based emails (2000s). [62]
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In probability and statistics, the logarithmic distribution (also known as the logarithmic series distribution or the log-series distribution) is a discrete probability distribution derived from the Maclaurin series expansion
ln(r) is the standard natural logarithm of the real number r. Arg(z) is the principal value of the arg function; its value is restricted to (−π, π]. It can be computed using Arg(x + iy) = atan2(y, x). Log(z) is the principal value of the complex logarithm function and has imaginary part in the range (−π, π].
The product of two Gaussian probability density functions (PDFs), though, is not in general a Gaussian PDF. Taking the Fourier transform (unitary, angular-frequency convention) of a Gaussian function with parameters a = 1 , b = 0 and c yields another Gaussian function, with parameters c {\displaystyle c} , b = 0 and 1 / c {\displaystyle 1/c ...
In probability theory, a logit-normal distribution is a probability distribution of a random variable whose logit has a normal distribution.If Y is a random variable with a normal distribution, and t is the standard logistic function, then X = t(Y) has a logit-normal distribution; likewise, if X is logit-normally distributed, then Y = logit(X)= log (X/(1-X)) is normally distributed.
All these extensions are also called normal or Gaussian laws, so a certain ambiguity in names exists. The multivariate normal distribution describes the Gaussian law in the k-dimensional Euclidean space. A vector X ∈ R k is multivariate-normally distributed if any linear combination of its components Σ k j=1 a j X j has a (univariate) normal ...
Here, and are the parameters of the distribution, which are the lower and upper bounds of the support, and is the natural log. The cumulative distribution function is F ( x ; a , b ) = ln ( x ) − ln ( a ) ln ( b ) − ln ( a ) for a ≤ x ≤ b . {\displaystyle F(x;a,b)={\frac {\ln(x)-\ln(a)}{\ln(b)-\ln(a)}}\quad {\text{ for ...