Exponentially modified Gaussian distribution
http://dbpedia.org/resource/Exponentially_modified_Gaussian_distribution an entity of type: WikicatCompoundDistributions
In probability theory, an exponentially modified Gaussian distribution (EMG, also known as exGaussian distribution) describes the sum of independent normal and exponential random variables. An exGaussian random variable Z may be expressed as Z = X + Y, where X and Y are independent, X is Gaussian with mean μ and variance σ2, and Y is exponential of rate λ. It has a characteristic positive skew from the exponential component. It may also be regarded as a weighted function of a shifted exponential with the weight being a function of the normal distribution.
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Exponentially modified Gaussian distribution
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EMG
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34299105
xsd:integer
1112655925
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x ∈ R
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density
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In probability theory, an exponentially modified Gaussian distribution (EMG, also known as exGaussian distribution) describes the sum of independent normal and exponential random variables. An exGaussian random variable Z may be expressed as Z = X + Y, where X and Y are independent, X is Gaussian with mean μ and variance σ2, and Y is exponential of rate λ. It has a characteristic positive skew from the exponential component. It may also be regarded as a weighted function of a shifted exponential with the weight being a function of the normal distribution.
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where
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is the CDF of a Gaussian distribution
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360
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λ > 0
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μ ∈ R
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σ2 > 0
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— mean of Gaussian component
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— rate of exponential component
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— variance of Gaussian component
xsd:integer
360
xsd:nonNegativeInteger
16599
