lognormal distribution

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log·nor·mal dis·tri·bu·tion

if a variable y is such that x = log y, it is said to have a lognormal distribution; this is a skew distribution.

lognormal distribution

see lognormal distribution.
References in periodicals archive ?
Thus, if P follows a GBM considering the initial value of P, then its future values P(t) have lognormal distributions with the mean and variance calculated using equations (8) and (9).
In this article, we assume that severity is modeled by lognormal distribution while frequency is modeled by Poisson distribution.
We characterized this uncertainty using statistical simulations from normal and lognormal distributions.
Note that the expression above matches the pdf of a mixture of three-parameter lognormal distributions, which is a generalization of the pdf given in (16), and we use the notation X ~ LSMIX([[lambda].
Here the lognormal distribution is used to check how the final result will change when distribution type is changed.
X] = daily sample mean for a given schedule and day type n = the number in the sample population r = vector of standard normal random numbers v = vector of correlated normal random numbers x = the schedule value for a given hour, day and schedule number [sigma] = scaling factor for lognormal distributions [mu] = location factor for lognormal distributions Subscripts i = hour j = day type k = schedule number
This allows us to compare model based on mixture of lognormal distributions with a standard Black-Scholes model.
The statistical metrics indicate that the FMM composed of Rayleigh and Lognormal distributions consistently ranked high in their ability to provide accurate statistical description for most of the impulses of channel impulse response.
According to KS criterion, the channel amplitudes are compatible mostly with both Weibull and Lognormal distributions, with a passing rate [greater than or equal to] 91%.
Tests using monthly data for individual firms are not consistent with lognormal distributions.
There is one Johnson (Su) for unbounded data, one for bounded on both tails (Sb), and one leading to the lognormal distributions (SI).