Represents a parameter that is normally distributed.
Namespace: Extreme.Statistics
Assembly: Extreme.Numerics (Extreme.Numerics)
Syntax
Methods
| Icon | Type | Description |
|---|---|---|
 | Equals(Object) | |
 | Finalize() | |
| GetConfidenceInterval(Double) |
Gets the confidence interval for the parameter at the specified confidence level.
|
| GetHashCode() | Serves as a hash function for a particular type. |
| GetTTest() |
Returns a OneSampleTTest object that can be used to perform further
analysis on the parameter.
|
| GetType() | Gets the Type of the current instance. |
| GetZTest() |
Returns a SimpleHypothesisTest object that can be used to perform further
analysis on the parameter.
|
| MemberwiseClone() | Creates a shallow copy of the current Object. |
| ToString() |
Returns a string representation of this instance.
|
Properties
| Icon | Type | Description |
|---|---|---|
 | Name |
Gets or sets the name of the parameter.
|
| PValue |
Gets the probability that the parameter is not zero.
|
| StandardError |
Gets the standard error of the parameter.
|
| Statistic |
Gets the value of the t-statistic for this parameter.
|
| Value |
Gets the estimated value of the parameter.
|
| Variable |
Remarks
Use the NormalParameter class to obtain more information about
a parameter of a GeneralLinearModel when the parameter
is normally distributed.
The Parameter class defines properties, including Statistic and PValue, that give an indication of the importance of the contribution of the corresponding variable to the model. Confidence intervals for the parameter can be obtained using the GetConfidenceInterval(Double) method. Further information can be obtained through the SimpleHypothesisTest returned by the GetZTest() method.
NormalParameter objects cannot be created directly. They are created by the statistical model and exposed through the model's Parameters collection. In particular, the parameters of a LogisticRegressionModel are traditionally assumed to be normally distributed.
Inheritance Hierarchy
