| 메소드 | 설명 | |
|---|---|---|
| Clone ( ) : object |
Creates a new object that is a copy of the current instance.
|
|
| DistributionFunction ( ) : double |
This method is not supported.
|
|
| Fit ( double observations, double weights ) : IDistribution |
Fits the underlying distribution to a given set of observations.
|
|
| Generate ( int samples ) : double[][] |
Generates a random vector of observations from the current distribution.
|
|
| NormalDistribution ( double mean, double covariance ) : System |
Constructs a multivariate Gaussian distribution with given mean vector and covariance matrix.
|
|
| NormalDistribution ( int dimension ) : System |
Constructs a multivariate Gaussian distribution with zero mean vector and unitary variance matrix.
|
|
| ProbabilityDensityFunction ( ) : double |
Gets the probability density function (pdf) for this distribution evaluated at point The Probability Density Function (PDF) describes the probability that a given value |
| public Fit ( double observations, double weights ) : IDistribution | ||
| observations | double | /// The array of observations to fit the model against. /// |
| weights | double | /// The weight vector containing the weight for each of the samples. /// |
| 리턴 | IDistribution | |
| public Generate ( int samples ) : double[][] | ||
| samples | int | The number of samples to generate. |
| 리턴 | double[][] | |
| public NormalDistribution ( double mean, double covariance ) : System | ||
| mean | double | |
| covariance | double | |
| 리턴 | System | |
| public NormalDistribution ( int dimension ) : System | ||
| dimension | int | |
| 리턴 | System | |
