Exponential Distribution
Where do you meet this distribution?
- The lengths of the inter-arrival times in a homogeneous Poisson process
- Nuclear physics : The time until a radioactive particle decays
- Statistical mechanics : Molecular distribution in uniform gravitational field
- Risk management : The time until default in reduced form credit risk modeling
Shape of Distribution
Basic Properties
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A parameter is required.
This parameter is Mean of the distribution.
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Continuous distribution defined on semi-infinite range
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This distribution is always asymmetric.
Probability
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Cumulative distribution function
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How to compute these on Excel.
A | B | |
---|---|---|
1 | Data | Description |
2 | 0.5 | Value for which you want the distribution |
3 | 8 | Value of parameter Beta |
4 | Formula | Description (Result) |
5 | =1-EXP(-A2/A3) | Cumulative distribution function for the terms above |
6 | =EXP(-A2/A3)/A3 | Probability density function for the terms above |
Quantile
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Inverse function of cumulative distribution function
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How to compute this on Excel.
A | B | |
---|---|---|
1 | Data | Description |
2 | 0.5 | Probability associated with the distribution |
3 | 1.7 | Value of parameter Beta |
4 | Formula | Description (Result) |
5 | =-A3*LN(1-A2) | Inverse of the cumulative distribution function for the terms above |
Characteristics
Mean -- Where is the "center" of the distribution? (Definition)
- Mean of the distribution is given as .
Standard Deviation -- How wide does the distribution spread? (Definition)
- Standard deviation of the distribution is given as .
Skewness -- Which side is the distribution distorted into? (Definition)
- Skewness is .
Kurtosis -- Sharp or Dull, consequently Fat Tail or Thin Tail (Definition)
- Kurtosis is .
Random Numbers
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Random number x is generated by inverse function method, which is for uniform random U,