Gumbel (Type I) Distribution
Where do you meet this distribution?
- Extreme value theory (EVT)
- Risk management -- Operational risk
Shape of Distribution
Basic Properties
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Two parameters are required (How can you get these).
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Continuous distribution defined on entire 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 Alpha |
4 | 2 | Value of parameter Beta |
5 | Formula | Description (Result) |
6 | =NTGUMBELDIST(A2,A3,A4,TRUE) | Cumulative distribution function for the terms above |
7 | =NTGUMBELDIST(A2,A3,A4,FALSE) | Probability density function for the terms above |
- Function reference : NTGUMBELDIST
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 | 0.7 | Probability associated with the distribution |
3 | 1.7 | Value of parameter Alpha |
4 | 0.9 | Value of parameter Beta |
5 | Formula | Description (Result) |
6 | =GUMBELINV(A2,A3,A4) | Inverse of the cumulative distribution function for the terms above |
- Function reference : NTGUMBELINV
Characteristics
Mean -- Where is the "center" of the distribution? (Definition)
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Mean of the distribution is given as
where is Euler's constant.
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How to compute this on Excel
A | B | |
---|---|---|
1 | Data | Description |
2 | 8 | Value of parameter Alpha |
3 | 2 | Value of parameter Beta |
4 | Formula | Description (Result) |
5 | =NTGUMBELMEAN(A2,A3) | Mean of the distribution for the terms above |
- Function reference : NTGUMBELMEAN
Standard Deviation -- How wide does the distribution spread? (Definition)
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Variance of the distribution is given as
where is Riemann zeta function.
Standard Deviation is a positive square root of Variance.
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How to compute this on Excel
A | B | |
---|---|---|
1 | Data | Description |
2 | 2 | Value of parameter Beta |
3 | Formula | Description (Result) |
4 | =NTGUMBELSTDEV(A2) | Standard deviation of the distribution for the terms above |
- Function reference : NTGUMBELSTDEV
Skewness -- Which side is the distribution distorted into? (Definition)
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Skewness of the distribution is given as
where is Riemann zeta function.
Kurtosis -- Sharp or Dull, consequently Fat Tail or Thin Tail (Definition)
- Kurtosis of the distribution is
Random Numbers
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Random number x is generated by inverse function method, which is for uniform random U,
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How to generate random numbers on Excel.
A | B | |
---|---|---|
1 | Data | Description |
2 | 0.5 | Value of parameter Alpha |
3 | 0.5 | Value of parameter Beta |
4 | Formula | Description (Result) |
5 | =NTRANDGUMBEL(100,A2,A3,0) | 100 Gumbel Type I deviates based on Mersenne-Twister algorithm for which the parameters above |
Note The formula in the example must be entered as an array formula. After copying the example to a blank worksheet, select the range A5:A104 starting with the formula cell. Press F2, and then press CTRL+SHIFT+ENTER.
NtRand Functions
- If you already have parameters of the distribution
- Generating random numbers based on Mersenne Twister algorithm: NTRANDGUMBEL
- Computing probability : NTGUMBELDIST
- Computing mean : NTGUMBELMEAN
- Computing standard deviation : NTGUMBELSTDEV
- Computing skewness : NTGUMBELSKEW
- Computing kurtosis : NTGUMBELKURT
- Computing moments above at once : NTGUMBELMOM
- If you know mean and standard deviation of the distribution
- Estimating parameters of the distribution:NTGUMBELRPARAM