Log |
public class LogNormalDistribution : NormalDistribution
The LogNormalDistribution type exposes the following members.
Name | Description | |
---|---|---|
LogNormalDistribution | Initializes a new instance of the LogNormalDistribution class | |
LogNormalDistribution(Double, Double) | Initializes a new instance of the LogNormalDistribution class | |
LogNormalDistribution(Double, Double, RandomGenerator) | Initializes a new instance of the LogNormalDistribution class |
Name | Description | |
---|---|---|
Generator | Returns the random generator used by the distribution to generate the random values. (Inherited from ProbabilityDistribution) | |
Mean | (Overrides NormalDistributionMean) | |
Stdev | (Overrides NormalDistributionStdev) |
Name | Description | |
---|---|---|
CDF | (Overrides NormalDistributionCDF(Double)) | |
Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) | |
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) | |
Initialize | ||
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
NextDouble | (Overrides NormalDistributionNextDouble) | |
(Overrides NormalDistributionPDF(Double)) | ||
Quantile | (Overrides NormalDistributionQuantile(Double)) | |
ToString | Returns a string that represents the current object. (Inherited from Object) |
Name | Description | |
---|---|---|
cached | (Inherited from NormalDistribution) | |
cacheval | (Inherited from NormalDistribution) | |
generator | Pointer to generator. (Inherited from ProbabilityDistribution) | |
m_log | ||
mu | (Inherited from NormalDistribution) | |
s_log | ||
scale | (Inherited from NormalDistribution) | |
sigma | (Inherited from NormalDistribution) |
Return log-normal distributed random deviates with given mean and standard deviation stdev according to the density function: 2 1 (ln x - m) p (x) dx = -------------- exp( - ------------ ) dx for x > 0 m,s sqrt(2 pi x) s 2 2 s = 0 otherwise where m and s are related to the arguments mean and stdev by: 2 mean m = ln ( --------------------- ) 2 2 sqrt( stdev + mean ) 2 2 stdev + mean s = sqrt( ln( -------------- ) ) 2 mean