Multivariate
Definition
Namespace: Extreme.Statistics.Distributions
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23
Overload List
| Multivariate | Constructs a new MultivariateNormalDistribution with mean equal to zero and standard deviation equal to 1. |
| Multivariate | Estimates the parameters of the distribution of a set of observations assuming it follows a multivariate normal distribution. |
| Multivariate | Constructs a new MultivariateNormalDistribution with specified mean and standard deviation equal to 1. |
| Multivariate | Estimates the parameters of the distribution of a variable assuming it follows a normal distribution. |
| Multivariate | Constructs a new MultivariateNormalDistribution with specified mean and standard deviation. |
MultivariateNormalDistribution(Int32)
Constructs a new MultivariateNormalDistribution with mean
equal to zero and standard deviation equal to 1.
public MultivariateNormalDistribution(
int order
)Parameters
- order Int32
Remarks
This constructor creates a standard normal distribution, with mean zero and standard deviation equal to one.
MultivariateNormalDistribution(Matrix<Double>)
Estimates the parameters of the distribution of a set of observations assuming it follows a multivariate normal distribution.
public MultivariateNormalDistribution(
Matrix<double> data
)Parameters
Return Value
The MultivariateNormalDistribution that best matches the distribution of the rows of data.Remarks
Use this constructor to create a MultivariateNormalDistribution whose parameters are estimated from data. This constructor uses an unbiased estimator.
Exceptions
| ArgumentNullException | data is null. |
MultivariateNormalDistribution(Vector<Double>)
Constructs a new MultivariateNormalDistribution with specified
mean and standard deviation equal to 1.
public MultivariateNormalDistribution(
Vector<double> mean
)Parameters
- mean Vector<Double>
- The mean of the distribution.
MultivariateNormalDistribution(Vector<Double>[])
Estimates the parameters of the distribution of a variable assuming it follows a normal distribution.
public MultivariateNormalDistribution(
Vector<double>[] variables
)Parameters
- variables Vector<Double>[]
- An array of vectors.
Return Value
The MultivariateNormalDistribution that best matches the distribution of variables.Remarks
Use this constructor to create a MultivariateNormalDistribution whose parameters are estimated from variables. This constructor uses an unbiased estimator.
Exceptions
| ArgumentNullException | variables is null. |
MultivariateNormalDistribution(Vector<Double>, Matrix<Double>)
Constructs a new MultivariateNormalDistribution with specified
mean and standard deviation.
public MultivariateNormalDistribution(
Vector<double> mean,
Matrix<double> covarianceMatrix
)Parameters
- mean Vector<Double>
- The mean of the distribution.
- covarianceMatrix Matrix<Double>
- A SymmetricMatrix<T> that specifies the variance-covariance matrix of the distribution.
Remarks
The standard deviation must be greater than zero.
Exceptions
| ArgumentNullException | mean is null.
-or- covarianceMatrix is null. |
| Dimension | The size of covarianceMatrix does not equal the length of mean. |