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Commands <br />4.4 Fill Time Series Data <br />TSTool Documentation <br />The Commands... Fill Time Series Data menu inserts commands for filling missing data in time series. <br />FillConstant(),.. Mill TS with constant> <br />FillDayTSFrom2MonthTSAndIDayTS ( }... Mill daily time series using DI = D2 *MI f M2> <br />FillFromTS()... Mill time series with values from another time series> <br />FillHistMonthAverageo ... Mill monthly TS using historic average> <br />FillHistVearAverageo ... Mill yearly TS using historic average> <br />FillInterpolateo ... Mill TS using interpolation> <br />FillMixedStationo ... Mill TS using mixed stations (under development)> <br />FIIIMOVE2()... Mill TS using MOVE2 method> <br />FillPattern(),.. <Fill TS using WETIDRVfAVG pattern> <br />FillProrate(),.. Mill TS by prorating another time series> <br />FillRegressiono ... <Fill TS using regression> <br />FillRepeato ... Mill TS by repeating values> <br />FillUsingDiversionCommentso ... <use diversion comments as data - HydroBase ONLV> <br />SetAutoExtendPerlodo ... <for data filling and manipulation> <br />SetAveragePeriodo ... <for data filling> <br />SetIgnoreLEZeroo ... <ignore values <= 0 in historical averages> <br />SetMissingDataValueo ... <for data filling> <br />SetPatternFlleo ... <For use with fillPattern() <br />SetRegressionPeriodo ... <for fillRegression()> <br />Commands... Fill Time Series Missing Data Menu <br />u Commands FillTimeSeries <br />Fill commands will only change values that are missing, whereas set commands (see next section) will <br />change values regardless of whether they are missing or non - missing. These commands can be executed <br />in sequence to apply multiple fill techniques to time series. Many commands accept the * wildcard for <br />the time series identifier, allowing all time series to be filled. <br />Time series may contain missing data due to the following reasons: <br />1. The data collection system is unavailable because of a failure, maintenance cycle, or hardware that is <br />turned off because of seasonal use <br />2. In a real -time system the most current data have not yet been received <br />3. Data collection hardware was not in place during a period (e.g., an early period) <br />4. Measured values are suspected of being in error and are changed to missing <br />5. Values in a computed time series cannot be computed (e.g., input data are missing) <br />6. A data source stores only observed values and non - recorded values are assumed to be missing rather <br />than a specific value (e.g., zero) <br />Observations that are available are typically either measured values or values that have been estimated by <br />the organization that collects and /or maintains the data. Data flags indicating missing data may or may <br />not be available in the original source data (e.g., an `m' or `e' character flag is often used to indicate <br />missing and estimated data). <br />Commands - 6 60 <br />