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Dataplot Vol 2 Vol 1

FREQUENCY TO RAW

Name:
    FREQUENCY TO RAW (LET)
Type:
    LET Subcommand
Purpose:
    Convert data in frequency format to raw format.
Description:
    At times, data will be collected in a frequency format (i.e., a value with a count of how many times that value occurred). However, you may want to use Dataplot commands that expect the data to be given in a single column format. For example, if X = 2.3 has a count of 20, the value of 2.3 will simply be repeated 20 times.

    Note that the maximum limit on the size of a Dataplot variables still applies. So if the sum of the counts array exceeds this limit, an error will be returned.

Syntax:
    LET <y> = FREQUENCY TO RAW <xval> <count>
                            <SUBSET/EXPCEPT/FOR qualification>
    where <xval> is a variable that contains the numeric values;
                <count> is a variable that contains the counts corresponding to <xval>;
                <y> is the variable to contain the raw data;
    and where the <SUBSET/EXCEPT/FOR qualification> is optional.
Examples:
    LET Y = FREQUENCY TO RAW XVAL XFREQ
Default:
    None
Synonyms:
    None
Related Commands:
    EXTEND = Extends a variable by another variable.
    LET = Creates, transforms, etc. a variable.
    STACK = Convert a set of response variables to a single response variable and a tag variable.
Applications:
    Data Management
Implementation Date:
    2004/5
Program:
     
    READ xval freq
    0  174
    1  112
    2  54
    3  14
    4  4
    5  1
    6  1
    END OF DATA
    LET Y = FREQUENCY TO RAW XVAL FREQ
    HERMITE MAXIMUM LIKELIHOOD Y
        
    The following output is generated.
      
                 HERMITE PARAMETER ESTIMATION:
      
     NUMBER OF OBSERVATIONS                  =      360
     SAMPLE MINIMUM                          =    0.000000
     SAMPLE MAXIMUM                          =    6.000000
     SAMPLE MEAN                             =   0.8027778
     SAMPLE VARIANCE                         =   0.9665661
      
     METHOD OF MOMENTS
           ESTIMATE OF ALPHA                 =   0.4047077
           ESTIMATE OF BETA                  =    1.578891
           ESTIMATE OF A                     =   0.6389894
           ESTIMATE OF B                     =   0.8189416E-01
           ESTIMATE OF VARIANCE OF A         =   0.6960734E-02
           ESTIMATE OF VARIANCE OF B         =   0.1518932E-02
           ESTIMATE OF COVARIANCE OF A AND B =  -0.2587889E-02
      
     METHOD OF EVEN POINTS
           SUM OF EVEN FREQUENCIES           =    233.0000
           SUM OF ODD FREQUENCIES            =    127.0000
           ESTIMATE OF ALPHA                 =   0.4375446
           ESTIMATE OF BETA                  =    1.397189
           ESTIMATE OF A                     =   0.6113325
           ESTIMATE OF B                     =   0.9572265E-01
      
     METHOD OF ZERO FREQUENCY AND MEAN
           ZERO FREQUENCY                    =    174.0000
           ESTIMATE OF ALPHA                 =   0.3891761
           ESTIMATE OF BETA                  =    1.673586
           ESTIMATE OF A                     =   0.6513197
           ESTIMATE OF B                     =   0.7572901E-01
           ESTIMATE OF VARIANCE OF A         =   0.5608298E-02
           ESTIMATE OF VARIANCE OF B         =   0.1160128E-02
           ESTIMATE OF COVARIANCE OF A AND B =   0.1899538E-02
      
     METHOD OF MAXIMUM LIKELIHOOD
           ESTIMATE OF ALPHA                 =   0.3950545
           ESTIMATE OF BETA                  =    1.637014
           ESTIMATE OF A                     =   0.6467096
           ESTIMATE OF B                     =   0.7803404E-01
           ESTIMATE OF VARIANCE OF ALPHA     =   0.7677542E-02
           ESTIMATE OF VARIANCE OF BETA      =   0.2727334
           ESTIMATE OF COVARIANCE OF
           ALPHA AND BETA                    =  -0.4439158E-01
      
        

Date created: 6/7/2004
Last updated: 6/7/2004
Please email comments on this WWW page to alan.heckert@nist.gov.