SEVSELECT Procedure
Parameter Initialization
PROC SEVSELECT enables you to initialize parameters of a model in different ways. A model can have two kinds of parameters: distribution parameters and regression parameters.
The distribution parameters can be initialized by using one of the following three methods:
- INIT= option
You can use the INIT= option in the DIST statement.
- INEST= option
You can use the INEST= data table in the PROC SEVSELECT statement.
- PARMINIT subroutine
You can define a dist_PARMINIT subroutine in the distribution model. For more information, see the section Defining a Severity Distribution Model with the FCMP Procedure.
Note that only one of the initialization methods is used. You cannot combine them. They are used in the following order:
-
The method that uses the INIT= option takes the highest precedence. If you use the INIT= option to provide an initial value for at least one parameter, then other initialization methods (INEST= or PARMINIT) are not used. If you specify initial values for some but not all the parameters by using the INIT= option, then the uninitialized parameters are initialized to the default value of 0.001.
If you use this option and if you specify the regression effects, then the value of the first distribution parameter must be related to the initial value for the base value of the scale or log-transformed scale parameter. For more information, see the section Estimating Regression Effects.
The method that uses the INEST= data table takes second precedence. If the INEST= data table contains a nonmissing value for even one distribution parameter, then the PARMINIT method is not used and any uninitialized parameters are initialized to the default value of 0.001.
If none of the distribution parameters are initialized by using the INIT= option or the INEST= data table, but the distribution model defines a PARMINIT subroutine, then PROC SEVSELECT invokes that subroutine with appropriate inputs to initialize the parameters. If the PARMINIT subroutine returns missing values for some parameters, then those parameters are initialized to the default value of 0.001.
If none of the initialization methods are used, each distribution parameter is initialized to the default value of 0.001.
For more information about regression models and initialization of regression parameters, see the section Estimating Regression Effects.
PARMINIT-Based Parameter Initialization Method and Distributed Data
If the input data are distributed across the computational nodes and if you use the PARMINIT subroutine to initialize the distribution parameters, then PROC SEVSELECT invokes that subroutine on each computational node with the data that are local to that node. The EDF estimates that are supplied to the PARMINIT subroutine are also computed using the local data. The initial values of the parameters that are supplied to the optimizer are the average of the local estimates that are computed on each node. This approach works well if the data are distributed randomly across nodes.