Gaussian distribution

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Gauss·i·an distribution

(gou′sē-ən)
n.

[After Karl Friedrich Gauss.]

Gaussian distribution

n
(Statistics) another name for normal distribution

nor′mal distribu′tion

n.
a theoretical frequency distribution represented by a normal curve. Also called Gaussian distribution.
ThesaurusAntonymsRelated WordsSynonymsLegend:
 Noun 1 Gaussian distribution - a theoretical distribution with finite mean and variancenormal distributiondistribution, statistical distribution - (statistics) an arrangement of values of a variable showing their observed or theoretical frequency of occurrencestatistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
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Properties of the modified Bessel function of the second kind related to the Poisson-Inverse Gaussian distribution may be found in Shoukri et al.
5 because the deployment area for the assumption of a Gaussian distribution of mobile locations has no edges.
At present, there are two main kinds of models for coating growth rate; a class of Gaussian distribution model [4, 5] and Cauchy distribution model [6] were proposed by Antonio and Freund, both of them belong to an infinite range model, and this kind of model is only suitable for the spray gun perpendicular to the surface of the workpiece.
Jitter caused by clock signals can be characterized by a Gaussian distribution [7].
It is modeled by adding each pixel a value from a zero-mean Gaussian distribution.
chi] is a random variable with a zero-mean Gaussian distribution and variance [[sigma].
0] direction is Gaussian distribution and kurtosis parameter equal 3.
Because the Kolmogorow-Smirnov test showed that results did not follow a gaussian distribution, the nonparametric Mann-Whitney U-test was used to evaluate the difference between the 2 means.
The Poisson-inverse Gaussian distribution is another widely used mixed Poisson distribution.
Class one has 200 samples from a bimodal Gaussian distribution, with centers at (1,0,0) and (-1,0,0).
1b) means that the Gaussian distribution overestimates the DEC2015 tail probability.
The standard cosmological model explains density fluctuations in matter in the early universe based on Gaussian distribution.

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