CategoricalGenLinModel overview
Public Instance Constructors
CategoricalGenLinModel Constructor
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Constructs a new CategoricalGenLinModel. |
Public Instance Properties
 CaseAnalysis | The case analysis. |
| CensorColumn | The column number in x which contains the interval type for each observation. |
| ClassificationVariableColumn | An index vector to contain the column numbers in x that are classification variables. |
| ClassificationVariableCounts | The number of values taken by each classification variable. |
| ClassificationVariableValues | The distinct values of the classification variables in ascending order. |
| ConvergenceTolerance | The convergence criterion. |
| CovarianceMatrix | The estimated asymptotic covariance matrix of the coefficients. |
| DesignVariableMeans | The means of the design variables. |
| ExtendedLikelihoodObservations | A vector indicating which observations are included in the extended likelihood. |
| FixedParameterColumn | The column number in x that contains a fixed parameter for each observation that is added to the linear response prior to computing the model parameter. |
| FrequencyColumn | The column number in x that contains the frequency of response for each observation. |
| Hessian | The Hessian computed at the initial parameter estimates. |
| InfiniteEstimateMethod | Specifies the method used for handling infinite estimates. |
| LastParameterUpdates | The last parameter updates (excluding step halvings). |
| LowerEndpointColumn | The column number in x that contains the lower endpoint of the observation interval for full interval and right interval observations. |
| MaxIterations | The maximum number of iterations allowed. |
| ModelIntercept | The intercept option. |
| NRowsMissing | The number of rows of data in x that contain missing values in one or more specific columns of x. |
| ObservationMax | The maximum number of observations that can be handled in the linear programming. |
| OptimizedCriterion | The optimized criterion. |
| OptionalDistributionParameterColumn | The column number in x that contains an optional distribution parameter for each observation. |
| Parameters | Parameter estimates and associated statistics. |
| Product | The inverse of the Hessian times the gradient vector computed at the input parameter estimates. |
| UpperBound | Defines the upper bound on the sum of the number of distinct values taken on by each classification variable. |
| UpperEndpointColumn | The column number in x that contains the upper endpoint of the observation interval for full interval and left interval observations. |
Public Instance Methods
| Equals (inherited from Object) | Determines whether the specified Object is equal to the current Object. |
| GetHashCode (inherited from Object) | Serves as a hash function for a particular type, suitable for use in hashing algorithms and data structures like a hash table. |
| GetType (inherited from Object) | Gets the Type of the current instance. |
| SetEffects | Initializes an index vector to contain the column numbers in x associated with each effect. |
| SetInitialEstimates | Sets the initial parameter estimates option. |
| Solve | Returns the parameter estimates and associated statistics for a CategoricalGenLinModel object. |
| ToString (inherited from Object) | Returns a String that represents the current Object. |
Protected Instance Methods
 Finalize (inherited from Object) | Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection. |
| MemberwiseClone (inherited from Object) | Creates a shallow copy of the current Object. |
See Also
CategoricalGenLinModel Class | Imsl.Stat Namespace | Example 1 | Example 2