OUTPUT
<OUT=SASdataset>
<keyword <=name>>…<keyword <=name>> </ options> ;
The OUTPUT statement creates a data set that contains observationwise statistics that are computed after the model is fitted.
The variables in the input data set are not included in the output data set to avoid data duplication for large data sets; however, variables that are specified in the
ID statement are included.
If the input data are in distributed form, where accessing data in a particular order cannot be guaranteed, the HPGENSELECT
procedure copies the distribution or partition key to the output data set so that its contents can be joined with the input
data.
The computation of the output statistics is based on the final parameter estimates. If the model fit does not converge, missing
values are produced for the quantities that depend on the estimates.
When there are more than two response levels for multinomial data, values are computed only for variables that are named by
the XBETA and PREDICTED keywords; the other variables have missing values. These statistics are computed for every response category, and the automatic
variable _LEVEL_
identifies the response category on which the computed values are based. If you also specify the OBSCAT option, then the observationwise statistics are computed only for the observed response category, as indicated by the value
of the _LEVEL_
variable.
For observations in which only the response variable is missing, values of the XBETA and PREDICTED statistics are computed even though these observations do not affect the model fit. For zeroinflated models, ZBETA and PZERO are also computed. This practice enables predicted mean values or predicted probabilities to be computed for new observations.
You can specify the following syntax elements in the OUTPUT statement before the slash (/).

OUT=SASdataset
DATA=SASdataset

specifies the name of the output data set. If the OUT= (or DATA=) option is omitted, the procedure uses the DATA
n convention to name the output data set.

keyword <=name>

specifies a statistic to include in the output data set and optionally assigns a name to the variable. If you do not provide a name, the HPGENSELECT procedure assigns a default name based on the type of statistic requested.
You can specify the following keywords for adding statistics to the OUTPUT data set:

ADJPEARSON  ADJPEARS  STDRESCHI

requests the Pearson residual, adjusted to have unit variance. The adjusted Pearson residual is defined for the ith observation as , where is the response distribution variance function and is the leverage. The leverage of the ith observation is defined as the ith diagonal element of the hat matrix
where is the diagonal matrix that has as the ith diagonal, and is a prior weight specified by a WEIGHT statement or 1 if no WEIGHT statement is specified. For the negative binomial, in the denominator is replaced with the distribution variance, in both the definition of the leverage and the adjusted residual.
This statistic is not computed for multinomial models, nor is it computed for zeromodified models.

LINP  XBETA

requests the linear predictor .

LOWER

requests a lower confidence limit for the predicted value. This statistic is not computed for generalized logit multinomial
models or zeromodified models.

PEARSON  PEARS  RESCHI

requests the Pearson residual, , where is the estimate of the predicted response mean and is the response distribution variance function. For the negative binomial defined in the section Negative Binomial Distribution and the zeroinflated models defined in the sections ZeroInflated Poisson Distribution and ZeroInflated Negative Binomial Distribution, the distribution variance is used in place of .
This statistic is not computed for multinomial models.

PREDICTED  PRED  P

requests predicted values for the response variable.

PZERO

requests zeroinflation probabilities for zeroinflated models.

RESIDUAL  RESID  R

requests the raw residual, , where is the estimate of the predicted mean. This statistic is not computed for multinomial models.

UPPER

requests an upper confidence limit for the predicted value. This statistic is not computed for generalized logit multinomial
models or zeromodified models.

ZBETA

requests the linear predictor for the zeros model in zeromodified models: .
You can specify the following options in the OUTPUT statement after the slash (/):