The HPCOUNTREG Procedure
-
Overview
- Getting Started
-
Syntax
-
DetailsMissing ValuesPoisson RegressionConway-Maxwell-Poisson RegressionNegative Binomial RegressionZero-Inflated Count Regression OverviewZero-Inflated Poisson RegressionZero-Inflated Conway-Maxwell-Poisson RegressionZero-Inflated Negative Binomial RegressionParameter Naming Conventions for the RESTRICT, TEST, BOUNDS, and INIT StatementsComputational ResourcesCovariance Matrix TypesDisplayed OutputOUTPUT OUT= Data SetOUTEST= Data SetODS Table Names
-
Examples
- References
OUTPUT Statement
-
OUTPUT <output-options> ;
The OUTPUT statement creates a new SAS data set that includes variables created by the output-options. These variables include the estimates of 
, the expected value of the response variable, and the probability of the response variable taking on the current value. Furthermore,
if a zero-inflated model was fit, you can request that the output data set contain the estimates of 
and the probability that the response is zero as a result of the zero-generating process. For the Conway-Maxwell-Poisson
model, the estimates of 
, 
, 
, 
, mode, variance, and dispersion are also available. Except for the probability of the current value, these statistics can
be computed for all observations in which the regressors are not missing, even if the response is missing. By adding observations
that have missing response values to the input data set, you can compute these statistics for new observations or for settings
of the regressors that are not present in the data without affecting the model fit.
You can specify only one OUTPUT statement. You can specify the following output-options:
- OUT=SAS-data-set
-
COPYVAR=SAS-variable-names
COPYVARS=SAS-variable-names - XBETA=name
-
PRED=name
MEAN=name -
names the variable to contain the predicted value of the response variable.
- PROB=name
-
names the variable to contain the probability that the response variable will take the actual value, Pr(
).
- PROBCOUNT(value1 <value2 …>)
-
outputs the probability that the response variable will take particular values. Each value should be a nonnegative integer. If you specify a noninteger, it is rounded to the nearest integer. The value can also be a list of the form X TO Y BY Z. For example, PROBCOUNT(0 1 2 TO 10 BY 2 15) requests predicted probabilities for counts 0, 1, 2, 4, 5, 6, 8, 10, and 15. This option is not available for the fixed-effects and random-effects panel models.
- ZGAMMA=name
- PROBZERO=name
-
names the variable to contain the value of
, which is the probability that the response variable will take the value of 0 as a result of the zero-generating process.
This variable is written to the output file only if the model is zero-inflated.
- GDELTA=name
-
assigns a name to the variable that contains estimates of
for the Conway-Maxwell-Poisson distribution.
- LAMBDA=name
-
assigns a name to the variable that contains the estimate of
for the Conway-Maxwell-Poisson distribution.
- NU=name
-
assigns a name to the variable that contains the estimate of
for the Conway-Maxwell-Poisson distribution.
- MU=name
-
assigns a name to the variable that contains the estimate of
for the Conway-Maxwell-Poisson distribution.
- MODE=name
-
assigns a name to the variable that contains the integral part of
(mode) for the Conway-Maxwell-Poisson distribution.
- VARIANCE=name
-
assigns a name to the variable that contains the estimate of variance for the Conway-Maxwell-Poisson distribution.
- DISPERSION=name
-
assigns a name to the variable that contains the value of dispersion for the Conway-Maxwell-Poisson distribution.