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alpar (Alpar Juttner)
alpar@cs.elte.hu
Pareto and Weibull random distributions
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1 file changed with 28 insertions and 1 deletions:
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    /// This function generates an exponential distribution random number
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    /// with mean <tt>1/lambda</tt>.
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    ///
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    double exponential(double lambda=1.0)
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    {
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      return -std::log(real<double>())/lambda;
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      return -std::log(1.0-real<double>())/lambda;
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    }
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    /// Gamma distribution with given integer shape
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    /// This function generates a gamma distribution random number.
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    /// 
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	    nu=V0*std::exp(-xi);
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	  }
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      } while(nu>std::pow(xi,delta-1.0)*std::exp(-xi));
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      return theta*(xi-gamma(int(std::floor(k))));
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    }
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    /// Weibull distribution
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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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    /// Pareto distribution
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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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    }  
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    ///@}
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    ///\name Two dimensional distributions
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    ///
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