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XLeratorDB/windowing Documentation

SQL Server moving population SKEW function


MovingSKEW_P

Updated: 30 Jun 2013


Use MovingSKEW_P to calculate the population skewness of column values in an ordered resultant table, without the need for a self-join. The population skewness is calculated for each value from the first value in the window to the last value in the window. If the column values are presented to the functions out of order, an error message will be generated.
Syntax
SELECT [westclintech].[wct].[MovingSKEW_P](
  <@Val, float,>
 ,<@Offset, int,>
 ,<@RowNum, int,>
 ,<@Id, tinyint,>
 ,<@Exact, bit,>)
Arguments
@Val
the value passed into the function. @Val is an expression of type float or of a type that can be implicitly converted to float.
@Offset           
specifies the window size. @Offset is an expression of type int or of a type that can be implicitly converted to int.
@RowNum
the number of the row within the group for which the population skewness is being calculated. If @RowNum for the current row in a set is less than or equal to the previous @RowNum and @RowNum is not equal to 1, an error message will be generated. @RowNum is an expression of type int or of a type that can be implicitly converted to int.
@Id
a unique identifier for the MovingSKEW_P calculation. @Id allows you to specify multiple moving population skewness calculations within a resultant table. @Id is an expression of type tinyint or of a type that can be implicitly converted to tinyint.
@Exact
a bit value which tells the function whether or not to return a NULL value if the number of rows in the window is smaller the @Offset value. If @Exact is 'True' and the number of rows in the window is less the @Offset then a NULL is returned. @Exact is an expression of type bit or of a type that can be implicitly converted to bit.
Remarks
·         If @Id is NULL then @Id = 0.
·         To calculate the population skewnesss from the beginning of a dataset or a partition, use the RunningSKEW_P function.
·         To calculate the population skewness for an entire data set or for an entire group within a data set use the SKEWNESS_P function.
·         If @RowNum is equal to 1, MovingSKEW_P is equal to zero
·         @RowNum must be in ascending order.
·         If @Exact IS NULL then @Exact = 'True'
·         There may be cases where the order in which the data are returned to the function and the order in which the results are returned are different, generally due to parallelism. You can use OPTION(MAXDOP 1) or OPTION(MAXDOP 1,FORCE ORDER) to help eliminate this problem.
Example
In this example, we have 20 rows of data and we want to caculate the population skewness of x and y over a window of 10 rows. Note that the @Id value for each MovingSKEW_P column is different. Since @Exact is NULL, NULL is returned when the window size is less than @Offset.
SELECT rn
,x
,y
,wct.MovingSKEW_P(x,10,ROW_NUMBER() OVER (ORDER BY RN), NULL, NULL) as [SKEW_P x]
,wct.MovingSKEW_P(y,10,ROW_NUMBER() OVER (ORDER BY RN), 1, NULL) as [SKEW_P y]
FROM (
      SELECT 1,101,117 UNION ALL
      SELECT 2,91,97 UNION ALL
      SELECT 3,96,121 UNION ALL
      SELECT 4,96,103 UNION ALL
      SELECT 5,86,74 UNION ALL
      SELECT 6,95,80 UNION ALL
      SELECT 7,91,105 UNION ALL
      SELECT 8,102,72 UNION ALL
      SELECT 9,94,108 UNION ALL
      SELECT 10,110,94 UNION ALL
      SELECT 11,121,85 UNION ALL
      SELECT 12,115,90 UNION ALL
      SELECT 13,112,96 UNION ALL
      SELECT 14,100,97 UNION ALL
      SELECT 15,124,106 UNION ALL
      SELECT 16,92,61 UNION ALL
      SELECT 17,92,107 UNION ALL
      SELECT 18,139,92 UNION ALL
      SELECT 19,95,101 UNION ALL
      SELECT 20,90,104
      )n(rn,x,y)
This produces the following result.
         rn           x           y               SKEW_P x               SKEW_P y
----------- ----------- ----------- ---------------------- ----------------------
          1         101         117                   NULL                   NULL
          2          91          97                   NULL                   NULL
          3          96         121                   NULL                   NULL
          4          96         103                   NULL                   NULL
          5          86          74                   NULL                   NULL
          6          95          80                   NULL                   NULL
          7          91         105                   NULL                   NULL
          8         102          72                   NULL                   NULL
          9          94         108                   NULL                   NULL
         10         110          94       0.59794064967205     -0.223688906272517
         11         121          85       1.14808763739985     0.0885382177825925
         12         115          90      0.631843870845252      0.224579774862171
         13         112          96      0.247845492717323     -0.137991148973669
         14         100          97      0.166326319556557     -0.103320897541807
         15         124         106      0.150533587918778     -0.411698835729833
         16          92          61      0.114791992347527     -0.841177595353945
         17          92         107       0.13688246083236     -0.807116763237067
         18         139          92      0.385280830439978      -1.25087766239486
         19          95         101      0.395585033305956      -1.41059257665943
         20          90         104      0.493903575245788      -1.44004210527361
 


This example uses the same data as the previous example, however @Exact has been set to
'FALSE'.
SELECT rn
,x
,y
,wct.MovingSKEW_P(x,10,ROW_NUMBER() OVER (ORDER BY RN), NULL, 'FALSE') as [SKEW_P x]
,wct.MovingSKEW_P(y,10,ROW_NUMBER() OVER (ORDER BY RN), 1, 'FALSE') as [SKEW_P y]
FROM (
      SELECT 1,101,117 UNION ALL
      SELECT 2,91,97 UNION ALL
      SELECT 3,96,121 UNION ALL
      SELECT 4,96,103 UNION ALL
      SELECT 5,86,74 UNION ALL
      SELECT 6,95,80 UNION ALL
      SELECT 7,91,105 UNION ALL
      SELECT 8,102,72 UNION ALL
      SELECT 9,94,108 UNION ALL
      SELECT 10,110,94 UNION ALL
      SELECT 11,121,85 UNION ALL
      SELECT 12,115,90 UNION ALL
      SELECT 13,112,96 UNION ALL
      SELECT 14,100,97 UNION ALL
      SELECT 15,124,106 UNION ALL
      SELECT 16,92,61 UNION ALL
      SELECT 17,92,107 UNION ALL
      SELECT 18,139,92 UNION ALL
      SELECT 19,95,101 UNION ALL
      SELECT 20,90,104
      )n(rn,x,y)
This produces the following result.
         rn           x           y               SKEW_P x               SKEW_P y
----------- ----------- ----------- ---------------------- ----------------------
          1         101         117                   NULL                   NULL
          2          91          97                   NULL                   NULL
          3          96         121                      0     -0.630903856710625
          4          96         103                      0    -0.0748700991297026
          5          86          74     -0.271545417883639     -0.579957911668973
          6          95          80     -0.400108877081824     -0.131152422955013
          7          91         105       -0.1387284841486     -0.296501322167989
          8         102          72     -0.146800156380065    -0.0797409447174199
          9          94         108     -0.102530483272052     -0.273202158161578
         10         110          94       0.59794064967205     -0.223688906272517
         11         121          85       1.14808763739985     0.0885382177825925
         12         115          90      0.631843870845252      0.224579774862171
         13         112          96      0.247845492717323     -0.137991148973669
         14         100          97      0.166326319556557     -0.103320897541807
         15         124         106      0.150533587918778     -0.411698835729833
         16          92          61      0.114791992347527     -0.841177595353945
         17          92         107       0.13688246083236     -0.807116763237067
         18         139          92      0.385280830439978      -1.25087766239486
         19          95         101      0.395585033305956      -1.41059257665943
         20          90         104      0.493903575245788      -1.44004210527361
 


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