
The Parameter Calculation Classes calculate regression parameters from input regression data. The Parameter Calculation Classes are contained in Table 2.
| Class Name | Description |
Holds information about adding observations to a parameter calculation object's base calculation. | |
Holds information about the addition of predictor variables to a parameter calculation object's base calculation. | |
Calculates the G statistic for a logistic model in comparison to the intercept only model. | |
Implements the calculation of linear regression parameters using QR decomposition. | |
Implements the calculation of linear regression parameters using QR decomposition with pivoting. | |
Implements the calculation of linear regression parameters using singular value decomposition. | |
Models an estimated linear regression parameter using a T distribution. Also used with a class instance to test some statistical hypothesis about the parameter's value. | |
A function object that takes the data and parameters associated with a linear regression model and returns the F statistic for that model. | |
Calculates several goodness of fit quantities, including the G statistic, Pearson statistic, and Hosmer-Lemeshow statistic along with their P-values and critical values. | |
Calculates model parameter estimates from logistic regression data using the iterative least squares method. | |
Calculates model parameter estimates from logistic regression data using the Levenberg-Marquardt method. | |
The container class for logistic regression parameter estimates and their associated statistical quantities. | |
Object contained in class RWRegression<T,S> and used by the class to perform parameter calculation. Also, the abstract base class for the parameter calculation classes. | |
Holds information regarding the removal of observations from a parameter calculation object's base calculation. | |
Contains information regarding the removal of predictor variables from a base parameter calculation object's base calculation. |
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