| ... | ... |
@@ -737,7 +737,7 @@ |
| 737 | 737 |
/// |
| 738 | 738 |
double exponential(double lambda=1.0) |
| 739 | 739 |
{
|
| 740 |
return -std::log(real<double>())/lambda; |
|
| 740 |
return -std::log(1.0-real<double>())/lambda; |
|
| 741 | 741 |
} |
| 742 | 742 |
|
| 743 | 743 |
/// Gamma distribution with given integer shape |
| ... | ... |
@@ -782,6 +782,33 @@ |
| 782 | 782 |
return theta*(xi-gamma(int(std::floor(k)))); |
| 783 | 783 |
} |
| 784 | 784 |
|
| 785 |
/// Weibull distribution |
|
| 786 |
|
|
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/// This function generates a Weibull distribution random number. |
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/// |
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///\param k shape parameter (<tt>k>0</tt>) |
|
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///\param lambda scale parameter (<tt>lambda>0</tt>) |
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/// |
|
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double weibull(double k,double lambda) |
|
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{
|
|
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return lambda*pow(-std::log(1.0-real<double>()),1.0/k); |
|
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} |
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|
|
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/// Pareto distribution |
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| 798 |
|
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/// This function generates a Pareto distribution random number. |
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/// |
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///\param x_min location parameter (<tt>x_min>0</tt>) |
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///\param k shape parameter (<tt>k>0</tt>) |
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/// |
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///\warning This function used inverse transform sampling, therefore may |
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///suffer from numerical unstability. |
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/// |
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///\todo Implement a numerically stable method |
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double pareto(double x_min,double k) |
|
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{
|
|
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return x_min*pow(1.0-real<double>(),1.0/k); |
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} |
|
| 785 | 812 |
|
| 786 | 813 |
///@} |
| 787 | 814 |
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