Represents a normal distribution.
Namespace: Extreme.Statistics.Distributions
Assembly: Extreme.Numerics (Extreme.Numerics)
Syntax
| Visual Basic (Declaration) |
|---|
Public Class NormalDistribution _ Inherits ContinuousDistribution |
| C# |
|---|
public class NormalDistribution : ContinuousDistribution |
| C++ |
|---|
public ref class NormalDistribution : public ContinuousDistribution |
Methods
| Icon | Type | Description |
|---|---|---|
  | DistributionFunction(Double, Double, Double) |
Evaluates the cumulative distribution function
(CDF) of this distribution for the specified value.
|
| DistributionFunction(Double) |
Evaluates the cumulative distribution function
(CDF) of this distribution for the specified value.
|
| Equals(Object) | |
 | Finalize() | |
| GetConfidenceInterval(Double, Double, Double) |
Returns a confidence interval at the specified level.
|
| GetExpectedHistogram(Double[](), Double) |
Gets a Histogram whose bins contain the expected number of samples
for a given total number of samples.
|
| GetExpectedHistogram(Double, Double, Int32, Double) |
Gets a Histogram whose bins contain the expected number of samples
for a given total number of samples.
|
| GetHashCode() | Serves as a hash function for a particular type. |
| GetRandomVariate(Random, Double) |
Returns a single random variate from a normal distribution
with specified mean and standard deviation equal to 1.
|
| GetRandomVariate(Random, Double, Double) |
Returns a single random variate from a normal distribution
with the specified parameters.
|
| GetRandomVariate(Random) |
Returns a random sample from the distribution.
|
| GetRandomVariates(Random, Vector) |
Fills a Vector with random numbers.
|
| GetRandomVariates(Random, Double[]()) |
Fills a Double array with random numbers.
|
| GetRandomVariates(Random, Double[](), Int32, Int32) |
Fills a Double array with random numbers.
|
| GetRandomVariates(Random, Vector, Int32, Int32) |
Fills a Double array with random numbers.
|
| GetType() | Gets the Type of the current instance. |
| InverseDistributionFunction(Double, Double, Double) |
Returns the inverse of the DistributionFunction(Double, Double, Double).
|
| InverseDistributionFunction(Double) |
Returns the sample value at the specified percentile.
|
| MemberwiseClone() | Creates a shallow copy of the current Object. |
| Probability(Double, Double) |
Returns the probability that a sample taken from the
distribution lies inside the specified interval.
|
| ProbabilityDensityFunction(Double) |
Returns the value of the probability density function
(PDF) of this distribution for the specified value.
|
| SurvivorDistributionFunction(Double) |
Evaluates the survivor distribution function
(SDF) of this distribution for the specified value.
|
| ToString() | |
| ZScore(Double) |
Returns the z-score of a sample.
|
Fields
| Icon | Type | Description |
|---|---|---|
 | Standard |
Represents the standard NormalDistribution.
|
Constructors
| Icon | Type | Description |
|---|---|---|
| NormalDistributionNew() |
Constructs a new NormalDistribution with mean
equal to zero and standard deviation equal to 1.
|
| NormalDistributionNew(Double) |
Constructs a new NormalDistribution with specified
mean and standard deviation equal to 1.
|
| NormalDistributionNew(Double, Double) |
Constructs a new NormalDistribution with specified
mean and standard deviation.
|
| NormalDistributionNew(NumericalVariable) |
Estimates the parameters of the distribution of a variable assuming it follows a normal distribution.
|
Properties
| Icon | Type | Description |
|---|---|---|
 | InterQuartileRange |
Returns the inter-quartile range of this distribution.
|
| IsSymmetrical |
Gets a value that indicates whether the distribution is known to be symmetrical around the mean.
|
| Kurtosis |
Gets the kurtosis of the distribution.
|
| Mean |
Gets the mean or expectation value of the distribution.
|
| Skewness |
Gets the skewness of the distribution.
|
| StandardDeviation |
Gets the standard deviation of the distribution.
|
| Variance |
Gets the variance of the distribution.
|
Remarks
Normal distributions are a family of distributions that have
the same general shape. They are symmetric with outcomes more
concentrated in the middle than in the tails. Normal
distributions are sometimes described as bell shaped.
The Mean of the distribution acts as the location parameter. The standard deviation (which equals the square root of the ) acts as the scale parameter. The normal distribution does not have a shape parameter.
Inheritance Hierarchy
System.Object
Extreme.Statistics.Distributions.Distribution
Extreme.Statistics.Distributions.ContinuousDistribution
Extreme.Statistics.Distributions.NormalDistribution
Extreme.Statistics.Distributions.Distribution
Extreme.Statistics.Distributions.ContinuousDistribution
Extreme.Statistics.Distributions.NormalDistribution
