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The DISCRIM Procedure |

An OUT= data set cannot be created if the DATA= data set is not an ordinary SAS data set.

An OUTD= data set cannot be created if the DATA= data set is not an ordinary SAS data set.

An OUTCROSS= data set cannot be created if the DATA= data set is not an ordinary SAS data set.

The OUTSTAT= data set contains the following variables:

- the BY variables, if any
- the CLASS variable
- _TYPE_, a character variable of length 8 that identifies the type of statistic
- _NAME_, a character variable of length 32 that identifies the row of the matrix, the name of the canonical variable, or the type of the discriminant function coefficients
- the quantitative variables, that is, those in the VAR statement, or, if there is no VAR statement, all numeric variables not listed in any other statement

**_TYPE_****Contents**- N
- number of observations both for the total sample (CLASS variable
missing) and within each class (CLASS variable present)
- SUMWGT
- sum of weights both for the total sample (CLASS
variable missing) and within each class (CLASS
variable present), if a WEIGHT statement is specified
- MEAN
- means both for the total sample (CLASS variable
missing) and within each class (CLASS variable present)
- PRIOR
- prior probability for each class
- STDMEAN
- total-standardized class means
- PSTDMEAN
- pooled within-class standardized class means
- STD
- standard deviations both for the total sample (CLASS variable
missing) and within each class (CLASS variable present)
- PSTD
- pooled within-class standard deviations
- BSTD
- between-class standard deviations
- RSQUARED
- univariate
*R*s^{2} - LNDETERM
- the natural log of the determinant or the natural log of the quasi-determinant of the within-class covariance matrix either pooled (CLASS variable missing) or not pooled (CLASS variable present)

**_TYPE_****Contents**- CSSCP
- corrected SSCP matrix both for the total sample (CLASS variable
missing) and within each class (CLASS variable present)
- PSSCP
- pooled within-class corrected SSCP matrix
- BSSCP
- between-class SSCP matrix
- COV
- covariance matrix both for the total sample (CLASS variable
missing) and within each class (CLASS variable present)
- PCOV
- pooled within-class covariance matrix
- BCOV
- between-class covariance matrix
- CORR
- correlation matrix
both for the total sample (CLASS variable missing)
and within each class (CLASS variable present)
- PCORR
- pooled within-class correlation matrix
- BCORR
- between-class correlation matrix

**_TYPE_****Contents**- CANCORR
- canonical correlations
- STRUCTUR
- canonical structure
- BSTRUCT
- between canonical structure
- PSTRUCT
- pooled within-class canonical structure
- SCORE
- standardized canonical coefficients
- RAWSCORE
- raw canonical coefficients
- CANMEAN
- means of the canonical variables for each class

**_TYPE_****Contents**- LINEAR
- coefficients of the linear discriminant functions
- QUAD
- coefficients of the quadratic discriminant functions

The values of the _NAME_ variable are as follows:

**_NAME_****Contents***variable names*- quadratic coefficients of the quadratic discriminant
functions (a symmetric matrix for each class)
- _LINEAR_
- linear coefficients of the discriminant functions
- _CONST_
- constant coefficients of the discriminant functions

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