Log |
The LogNormal type exposes the following members.
Methods| Name | Description | |
|---|---|---|
  | CDF | Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). |
| CumulativeDistribution | Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). |
| Density | Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. |
| DensityLn | Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). |
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) |
| Estimate | Estimates the log-normal distribution parameters from sample data with maximum-likelihood. |
 | Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object) |
| GetHashCode | Serves as the default hash function. (Inherited from Object) |
| GetType | Gets the Type of the current instance. (Inherited from Object) |
| InvCDF | Computes the inverse of the cumulative distribution function (InvCDF) for the distribution at the given probability. This is also known as the quantile or percent point function. |
| InverseCumulativeDistribution | Computes the inverse of the cumulative distribution function (InvCDF) for the distribution at the given probability. This is also known as the quantile or percent point function. |
| IsValidParameterSet | Tests whether the provided values are valid parameters for this distribution. |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) |
| Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. | |
| PDFLn | Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). |
| Sample | Generates a sample from the log-normal distribution using the Box-Muller algorithm. |
| Sample(Double, Double) | Generates a sample from the log-normal distribution using the Box-Muller algorithm. |
| Sample(Random, Double, Double) | Generates a sample from the log-normal distribution using the Box-Muller algorithm. |
| Samples | Generates a sequence of samples from the log-normal distribution using the Box-Muller algorithm. |
| Samples(Double) | Fills an array with samples generated from the distribution. |
| Samples(Double, Double) | Generates a sequence of samples from the log-normal distribution using the Box-Muller algorithm. |
| Samples(Double, Double, Double) | Fills an array with samples generated from the distribution. |
| Samples(Random, Double, Double) | Generates a sequence of samples from the log-normal distribution using the Box-Muller algorithm. |
| Samples(Random, Double, Double, Double) | Fills an array with samples generated from the distribution. |
| ToString |
A string representation of the distribution.
(Overrides ObjectToString) |
| WithMeanVariance | Constructs a log-normal distribution with the desired mean and variance. |
| WithMuSigma | Constructs a log-normal distribution with the desired mu and sigma parameters. |
See Also