Abstract
The problem introduced in this paper originated from a water pollution study of the Menomenee River in Milwaukee, Wisconsin. The final goal of the study was to estimate the total pollutant load deposited in Lake Michigan, for a given season. However, the information on the concentration of pollutants was not complete. Concentration data were available for only 20% of the days in the study period. Complete data were available on two related series: river flow rate and water equivalent of precipitation. Those series were used along with the pollutant concentration data to create a model for pollutant behavior (for the different pollutants and years), to estimate the missing observations and to estimate total pollutant loading for several seasons. (See Miller, et al (1980).)
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© 1984 Springer-Verlag Berlin Heidelberg
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Miller, R.B., Ferreiro, O. (1984). A Strategy to Complete a Time Series with Missing Observations. In: Parzen, E. (eds) Time Series Analysis of Irregularly Observed Data. Lecture Notes in Statistics, vol 25. Springer, New York, NY. https://doi.org/10.1007/978-1-4684-9403-7_12
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DOI: https://doi.org/10.1007/978-1-4684-9403-7_12
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