Time Interval Accumulation Settings

Specify how you want the data to be accumulated within each time interval. Accumulation combines data within the same time interval into a summary value for that time period. Accumulation can be used in the following situations:

Let r equals . the set , r sub q end set with subscript q equals 1 , and with superscript q , end sub-superscript. Click image for alternative formats. be the data vector ordered by the time series occurrence in the data set with respect to the observation index. Let q equals 1 comma dot dot dot comma q. Click image for alternative formats. be the index that represents this ordering. Let QN be the number of nonmissing values and let q sub n m i s s end sub . equals q minus , q sub n. Click image for alternative formats. be the number of missing values in the data vector. Let r with macron above , equals , fraction 1 , over q sub n end fraction . cap sigma with q equals 1 below and with q above . r sub q. Click image for alternative formats. be the average value of the data vector with the missing values ignored.

The following example accumulates the observation series z super open n close end super . equals . the set , z sub i end set with subscript i equals 1 , and with superscript n , end sub-superscript. Click image for alternative formats. to the time series y super open t close end super . equals . the set , y sub t end set with subscript t equals 1 , and with superscript t , end sub-superscript . comma , y sub t , equals eh c c u m u l eh t e open . z with subscript t , and with superscript open t close , end sub-superscript . close. Click image for alternative formats., for t equals 1 comma dot dot dot comma t. Click image for alternative formats.. In this situation, r equals . z with subscript t , and with superscript open t close , end sub-superscript. Click image for alternative formats. and q equals . n with subscript t , and with superscript open t close , end sub-superscript. Click image for alternative formats. for t equals 1 comma dot dot dot comma t. Click image for alternative formats..

Let eh equals eh c c u m u l eh t e open r close. Click image for alternative formats. be this accumulated value for this data vector when the following accumulationeither of two processes that are used to convert a time series. (1) Accumulation converts a time series that has no fixed interval into a time series that does have a fixed interval (such as hourly or monthly). (2) Accumulation converts a time series that has a fixed interval into a time series with a lower frequency time interval (such as hourly into daily). Accumulation combines data within the same time interval into a summary value for that time period. methods are applied:

Average of Values

accumulates the vector values based on the average of their values.

eh equals , r with macron above , equals , fraction 1 , over q sub n end fraction . cap sigma with q equals 1 below and with q above . r sub q. Click image for alternative formats.

Missing values are ignored in the summation. If q sub n , equals 0. Click image for alternative formats., then a is set to missing.

Corrected Sum of Squares

accumulates the vector values based on their corrected sum of squares.

eh equals . cap sigma with q equals 1 below and with q above . open , r sub q , negative , r with macron above , close squared. Click image for alternative formats.

Missing values are ignored in the summation. If q sub n , equals 0. Click image for alternative formats., then a is set to missing.

Maximum of Values

accumulates the vector values based on the maximum of their values.

eh equals mehx of open . the set , r sub q end set with subscript q equals 1 , and with superscript q , end sub-superscript . close. Click image for alternative formats.

Missing values are ignored in the summation. If q sub n , equals 0. Click image for alternative formats., then a is set to missing.

Minimum of Values

accumulates the vector values based on the minimum of their values.

eh equals min of open . the set , r sub q end set with subscript q equals 1 , and with superscript q , end sub-superscript . close. Click image for alternative formats.

Missing values are ignored in the summation. If q sub n , equals 0. Click image for alternative formats., then a is set to missing.

Number of non-missing values

accumulates the vector values based on the number of nonmissing values.

eh equals , q sub n. Click image for alternative formats.
Number of Missing values

accumulates the vector values based on the number of missing values.

eh equals . q sub n m i s s end sub. Click image for alternative formats.
Standard Deviation of Values

accumulates the vector values based on their standard deviation.

eh equals . square root of fraction 1 , over q sub n , minus 1 end fraction . cap sigma with q equals 1 below and with q above . open , r sub q , minus , r with macron above , close squared end root. Click image for alternative formats.

Missing values are ignored in the summation. If q sub n , less than or equal to 1. Click image for alternative formats., then a is set to missing.

Sum of Values

accumulates the vector values based on the summation of their values.

eh equals . cap sigma with q equals 1 below and with q above . r sub q. Click image for alternative formats.

Missing values are ignored in the summation. If q sub n , equals 0. Click image for alternative formats., then a is set to missing.

Uncorrected Sum of Squares

accumulates the vector values based on their uncorrected sum of squares.

eh equals . cap sigma with q equals 1 below and with q above . open , r sub q , close squared. Click image for alternative formats.

Missing values are ignored in the summation. If q sub n , equals 0. Click image for alternative formats., then a is set to missing.

Last updated: March 16, 2026