
DIFFERENCE OF HODGESLEHMANNName:
Specifically, the HodgesLehmann estimate for location is defined as
Dataplot uses ACM algorithm 616 (HLQEST written by John Monohan) to compute the estimate. This is a fast, exact algoirthm. One modification is that for n <= 25 Dataplot computes the estimate directly from the definition. For the difference of the HodgesLehmann location estimats, the HodgesLehmann location estimate is computed for each of two samples then their difference is taken.
<SUBSET/EXCEPT/FOR qualification> where <y1> is the first response variable; <y2> is the first response variable; <par> is a parameter where the computed difference of the HodgesLehmann location estimate is stored; and where the <SUBSET/EXCEPT/FOR qualification> is optional.
LET A = DIFFERENCE OF HODGESLEHMANN Y1 Y2 SUBSET X > 1
Rand Wilcox (1997), "Introduction to Robust Estimation and Hypothesis Testing," Academic Press,
SKIP 25 READ IRIS.DAT Y1 TO Y4 X . LET A = DIFFERENCE OF HODGESLEHMANN Y1 Y2 TABULATE DIFFERENCE OF HODGESLEHMANN Y1 Y2 X . XTIC OFFSET 0.2 0.2 X1LABEL GROUP ID Y1LABEL DIFFERENCE OF HODGESLEHMANN CHAR X LINE BLANK DIFFERENCE OF HODGESLEHMANN PLOT Y1 Y2 X CHAR X ALL LINE BLANK ALL BOOTSTRAP DIFFERENCE OF HODGESLEHMANN PLOT Y1 Y2 XDataplot generated the following output. ************************************************** ** LET A = DIFFERENCE OF HODGES LEHMANN Y1 Y2 ** ************************************************** THE COMPUTED VALUE OF THE CONSTANT A = 0.27500002E+01 ***************************************************** ** TABULATE DIFFERENCE OF HODGES LEHMANN Y1 Y2 X ** ***************************************************** * Y1 AND Y2 X * DIFFERENCE OF HODGESLEHMANN ********************************************** 1.00000 * 1.60000 2.00000 * 3.10000 3.00000 * 3.60000 GROUPID AND STATISTIC WRITTEN TO FILE DPST1F.DAT  
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Date created: 03/27/2003 