Examples - pi.science.distribution.PIPoissonDistribution
1. How to compute Poisson distribution propability for X (lambda=1) ?
PIPoissonDistribution distribution = new PIPoissonDistribution();
Console.WriteLine( "Probability for x=0.0 : " + distribution.GetCDF( 0.0 ) );
Console.WriteLine( "Probability for x=1.0 : " + distribution.GetCDF( 1.0 ) );
Console.WriteLine( "Probability for x=3.0 : " + distribution.GetCDF( 3.0 ) );
Console.WriteLine( "Probability for x=5.0 : " + distribution.GetCDF( 5.0 ) );
Output:
Probability for x=0.0 : 0,367879441171442
Probability for x=1.0 : 0,735758882342885
Probability for x=3.0 : 0,981011843123846
Probability for x=5.0 : 0,999405815182418
2. How to compute X for Poisson distribution propability ?
PIPoissonDistribution distribution = new PIPoissonDistribution();
Console.WriteLine( "X value for probability for prob=0.7358 : " + distribution.GetXForProbability( 0.7358 ) );
Console.WriteLine( "X value for probability for prob=0.9810 : " + distribution.GetXForProbability( 0.9810 ) );
Console.WriteLine( "X value for probability for prob=0.9994 : " + distribution.GetXForProbability( 0.9994 ) );
Console.WriteLine( "X value for probability for prob=1 : " + distribution.GetXForProbability( 1 ) );
Output:
X value for probability for prob=0.7358 : 1
X value for probability for prob=0.9810 : 3
X value for probability for prob=0.9994 : 5
X value for probability for prob=1 : 9
3. How to compute Poisson probability density for X (=curve points) ?
PIPoissonDistribution distribution = new PIPoissonDistribution();
Console.WriteLine( "x=0.1 : " + distribution.GetPDF( 0.1 ) );
Console.WriteLine( "x=0.5 : " + distribution.GetPDF( 0.5 ) );
Console.WriteLine( "x=1.0 : " + distribution.GetPDF( 1.0 ) );
Console.WriteLine( "x=2.0 : " + distribution.GetPDF( 2.0 ) );
Console.WriteLine( "x=5.0 : " + distribution.GetPDF( 5.0 ) );
Output:
x=0.1 : 0,367879441171442
x=0.5 : 0,367879441171442
x=1.0 : 0,367879441171442
x=2.0 : 0,183939720585721
x=5.0 : 0,00306566200976202
