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exponential distribution

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exponential distribution

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Also known as lifetime distribution

probability distribution

Key facts

Parameters
0,"}}'> λ > 0 , {\displaystyle \lambda >0,} rate, or inverse scale
Support
x ∈ [ 0 , ∞ ) {\displaystyle x\in [0,\infty )}
Pdf
λ e − λ x {\displaystyle \lambda e^{-\lambda x}}
Cdf
1 − e − λ x {\displaystyle 1-e^{-\lambda x}}
Quantile
− ln ⁡ ( 1 − p ) λ {\displaystyle -{\frac {\ln(1-p)}{\lambda }}}
Mean
1 λ {\displaystyle {\frac {1}{\lambda }}}
Median
ln ⁡ 2 λ {\displaystyle {\frac {\ln 2}{\lambda }}}
Mode
0 {\displaystyle 0}
Variance
1 λ 2 {\displaystyle {\frac {1}{\lambda ^{2}}}}
Skewness
2 {\displaystyle 2}
Excess kurtosis
6 {\displaystyle 6}
Entropy
1 − ln ⁡ λ {\displaystyle 1-\ln \lambda }
Mgf
λ λ − t , for t < λ {\displaystyle {\frac {\lambda }{\lambda -t}},{\text{ for }}t<\lambda }
Cf
λ λ − i t {\displaystyle {\frac {\lambda }{\lambda -it}}}
Fisher information
1 λ 2 {\displaystyle {\frac {1}{\lambda ^{2}}}}
Kullback leibler divergence
ln ⁡ λ 0 λ + λ λ 0 − 1 {\displaystyle \ln {\frac {\lambda _{0}}{\lambda }}+{\frac {\lambda }{\lambda _{0}}}-1}

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Exponential distribution cdf - public domain.svg
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Exponential distribution
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Article

In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate; the distance parameter could be any meaningful mono-dimensional measure of the process, such as time between production errors, or length along a roll of fabric in the weaving manufacturing process. It is a particular case of the gamma distribution. It is the continuous analogue of the geometric distribution, and it has the key property of being memoryless. In addition to being used for the analysis of Poisson point processes it is found in various other contexts.

The exponential distribution is not the same as the class of exponential families of distributions. This is a large class of probability distributions that includes the exponential distribution as one of its members, but also includes many other distributions, such as the normal, binomial, gamma, and Poisson distributions.

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