Gaussian distribution

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Related to Gaussian Distributions: Gaussian random variable

Gauss·i·an distribution

 (gou′sē-ən)
[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:
Noun1.Gaussian distribution - a theoretical distribution with finite mean and variance
distribution, statistical distribution - (statistics) an arrangement of values of a variable showing their observed or theoretical frequency of occurrence
statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
References in periodicals archive ?
Because the GMM is the linear combination of K independent Gaussian distributions (or K components), the probability density function (PDF) of a Gaussian distribution is modelled as
Figure 4(a) represents Gaussian distributions of the Shannon entropy generated by (7) and (8) as the two concentric circles labeled as burst and suppression, respectively.
Minimum distance is stated as difference of Gaussian distributions.
We have economic reason to expect that inside each of the regimes the steps are independently distributed but during empirical measurements we cannot separate more Gaussian distributions to do a mix.
Possible choices of the distribution of W are the Gaussian, Gamma and inverse Gaussian distributions.
4d, the probability distribution of the fluctuating wind speed obtained based WT from tower original wind sample 2 (22:10-02:48, 1-2 April 2003) complies with Gaussian distribution well, but the results obtained based EMD and traditional stationary model deviate from the Gaussian distributions significantly.
With truly Gaussian distributions, measurements that appear extraordinary, such as a person a mile tall, are probably flukes; perhaps the measurer didn't know how to use a ruler or made a mistake in writing down the number.
Samples from the Gaussian distributions give the weights for the RBF.
Extensively tested in classroom teaching, topics include an introduction to Dirichlet distribution, exponential families, and their applications; a detailed description of learning algorithms and conditional Gaussian distributions using junction tree methods; and a discussion of Pearl's intervention calculus with an introduction to the notion of "see" and "do" conditioning.
The software quickly calculates: (a) the mean value and the standard deviation of all the measurement values; (b) the Log-Normal distribution; (c) the Gaussian distribution; (d) the deviations from the Log-Normal and Gaussian distributions in terms of the Kolmogoroff-Smirnov and Chi-square tests; (e) skewness; and (f) excess of the measured distribution.