option. In the COST= option, you may not use abbreviated variable lists such as D1-D3,
ABC--XYZ, or PQR:.
Default:
All costs are assumed to be 0.
CAUTION:
The COST= option may only be specified when the DECDATA= data set is of
TYPE=REVENUE.
PRIORVAR=variable
Specifies the variable in the DECDATA= data set that contains the prior probabilities to use for
making decisions.
Default:
None
Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
The DMREG Procedure
FREQ Statement
Specifies the variable that contains frequencies for training data.
FREQ <
variable> ;
variable
Specifies the frequency variable. If specified, the FREQ variable overrides whatever is in the
DMDB metadata. If the FREQ statement contains no name, then a FREQ variable is not used.
CAUTION:
If there is a frequency variable in the DMDB, it is not advisable to use another
variable as a frequency variable because the training data does not contain
observations with invalid values in the FREQ variable specified in the DMDB. For
example, if the frequency variable specified in the DMDB contains a 0 or negative
value, then that observation is discarded even if the FREQ variable that you specified
in the FREQ statement of the DMREG procedure contains valid frequency values.
Default:
If the FREQ statement is not specified, the frequency variable in the DMDB
is used. If the FREQ statement is specified without a variable, a frequency of
1 is used for all observations.
Range:
The frequency variable can contain integer or non-integer values.
Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
The DMREG Procedure
MODEL Statement
Specifies modeling options.
Requirements: Model statement is required.
MODEL dependent=independent(s) / model-option(s);
Required Argument
dependent=independent(s)
where the arguments are defined as follows:
dependent
Specifies the response variable (target).
independents
Specifies the explanatory variables or effects (inputs). The syntax of effects is described in .
Options
model-options(s)
Specifies options that affect the fit, confidence intervals, variable selection, and specification of
the model as follows:
MODEL Options - Fitting Options
MISCCONV=n
Specifies the critical misclassification rate at which to stop iterations.
Default:
n = 0
Range:
0 - 1
STARTMISC=n
Specifies the number of iterations to be processed before checking misclassification rate.
Default:
Depends on the optimization technique:
n = 3
TECHNIQUE = NEWRAP, NRRIDG, TRUREG
n = 5
TECHNIQUE = QUANEW, DBLDOG
n = 10
TECHNIQUE = CONGRA
Alias:
STATMISC
MODEL Options - Miscellaneous Options
ALPHA=n
Specifies the significance level of confidence intervals for regression parameters.
Default:
.05
CLPARM
Specifies the computation of confidence intervals for parameters.
CORRB
Specifies that the correlation matrix is to be printed.
COVB
Specifies that the covariance matrix is to be printed.
MODEL Options - Selection Options
CHOOSE=AIC | NONE | SBC | TDECDATA | VDECDATA | VERROR | VMISC | XDECDATA |
XERROR | XMISC
Specifies the criterion for the selection of the model.
AIC
Represents the Akaike Information Criterion. The model with the smallest criterion value is
chosen.
NONE
Chooses standard variable selection based on the entry and/or stay
P-values.
SBC
Represents the Schwarz Bayesian Criterion. The model with the smallest criterion value is
chosen.
TDECDATA
Represents the total profit/loss for the training data. The model with the largest profit or the
smallest loss is chosen.
VDECDATA
Represents the total profit/loss for the VALIDATA= data set. The model with the largest
profit or the smallest loss is chosen.
VERROR
Represents the error rate for the VALIDATA= data set. The error is the sum of square
errors for least-square regression and negative log-likelihood for logistic regression. The
model with the smallest error rate is chosen.
VMISC
Represents the misclassification rate for the VALIDATA= data set.
The model with the
smallest misclassification rate is chosen.
XDECDATA
Represents the total profit/loss for cross-validation of the training data. The model with the
largest profit or the smallest loss is chosen.
XERROR
Represents the error rate for cross validation. The error is the sum of square errors for
least-square regression and negative log-likelihood for logistic regression. The model with
the smallest error rate is chosen.
XMISC
Represents the misclassification rate for cross validation. The model with the smallest
misclassification rate is chosen.
Default:
If decision processing is specified, the default is CHOOSE=TDECDATA; if
the VALIDATA= data set is also specified, the default is
CHOOSE=VDECDATA.
DETAILS
Prints details at each model selection step.
HIERARCHY=ALL | CLASS
Specifies how containment is to be applied.
ALL
Specifies that all independent variables that meet hierarchical requirements are included in
the model.
CLASS
Specifies that only CLASS variables that meet hierarchical requirements are included in the
model.
Default:
ALL
INCLUDE=n
Specifies that the first n effects in the model are to be included in each model.
Default:
0