The arboretum procedure



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The STDIZE Procedure

FREQ Statement

Specifies a numeric variable whose values represent the frequency of the observation.

Discussion: If one variable in the input data set represents the frequency of occurrence for other

values in the observation, specify the variable's name in a FREQ statement. PROC

STDIZE then treats the data set as if each observation appeared n times, where n is the

value of the FREQ variable for the observation.



Alias: FREQUENCY

FREQ variable;

Required Argument

variable

Specifies a single numeric variable whose value represents the frequency of the observation. If

you use the FREQ statement, the procedure assumes that each observation represents n

observations, where n is the value of variable.



Range:

If variable is not an integer, the SAS System truncates it to the largest integer

less than the FREQ value. If variable is less than 1 or is missing, the

procedure does not use that observation to calculate statistics. The sum of the

frequency variable represents the total number of observations and cannot

exceed 2


31

.

Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.




The STDIZE Procedure

LOCATION Statement

Specifies the list of numeric variables that contain location measures in the input data set of

METHOD=IN.

LOCATION variable(s);

Required Argument

variable(s)

Specifies one or more variables that contain location measures in the input data set identified by

the METHOD=IN(SAS-data-set).

Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.




The STDIZE Procedure

SCALE Statement

Specifies the list of numeric variables that contain scale measures in the input data set of

METHOD=IN.

SCALE variable(s);

Required Argument

variable(s)

Identifies one or more variables that contain scale measures in the input data set identified by the

METHOD=IN(SAS-data-set).

Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.




The STDIZE Procedure

VAR Statement

Specifies a list of variables to be standardized.

Alias: VARIABLE

Default: If the VAR statement is omitted, all numeric variables not specified in the BY=, FREQ=,

LOCATION=, SCALE=, or WEIGHT= lists are standardized.



VAR variable(s);

Required Argument

variable(s)

Identifies one or more variables to be standardized.

Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.



The STDIZE Procedure

WEIGHT Statement

Specifies a single numeric weight in the input SAS data set whose values are used to weight each

observation. Only one variable can be specified.

Alias: WGT

WEIGHT variable;

Required Argument

variable

Specifies a numeric variable whose value weights the analysis variables in each observation. The

variable does not have to be an integer. If the value of variable is less than 0 or is missing, the

procedure uses a value of 0.



Discussion:

The sample mean and (uncorrected) sample variances are computed as:

where 

 is the weight value of the  th observation, 



 is the value of the  th

observation, and   is the divisor controlled by the VARDEF=option (see

VARDEF= option for details).

MEAN


the weighted mean 


SUM

the weighted sum 

USTD

the weighted uncorrected standard deviation



STD

the weighted standard deviation, 

EUCLEN

The weighted Euclidean length is computed as the weighted squared



root of uncorrected sum of squares:

AGK


Refers to the weight statement in PROC ACECLUS for how weight is

applied to the AGK estimate (METHOD=COUNT) option.

L

Refers to the weight statement in PROC FASTCLUS for how weight is



used to compute weighted cluster means (LEAST= option). Note that

the number of clusters is always 1.



Range:

The WEIGHT variable values can be non-integers. An observation is used in

the analysis only if the value of the WEIGHT variable is greater than 0.

Tip:

The WEIGHT variable only affects METHOD=MEAN, SUM, EUCLEN,

USTD, STD, AGK, and L calculations.

Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.




The STDIZE Procedure

Details

Standardization Methods

The following table lists standardization methods and their corresponding location and scale measures

that are available in the METHOD= option.

Table of Methods for Computing Location and Scale

Measures

METHOD

SCALE

LOCATION

ABW(c)

Biweight

A-estimate

Biweight 1-step

M-estimate

AGK(p)

AGK


estimate

(ACECLUS)

Mean

AHUBER (c)



Huber

A-estimate

Huber 1-step

M-estimate

AWAVE (c)

Wave


A-estimate

Wave 1-step M

estimate

EUCLEN


Euclidean

length


0

IN(SAS-data-set)

Read from

the data set

Read from the

data set


IQR

Interquartile

range

Median


LEAST

L(p)

L(p)

MAD


Median

absolute


deviation

from the


median

Median





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