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Interpolating Time Series with Application to the Estimation of Holiday Effects on Electricity Demand
Author(s) -
Brubacher S. R.,
Wilson G. Tunnicliffe
Publication year - 1976
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2346678
Subject(s) - estimation , series (stratigraphy) , electricity demand , econometrics , electricity , time series , statistics , economics , computer science , mathematics , operations research , engineering , electricity generation , power (physics) , electrical engineering , geology , management , paleontology , physics , quantum mechanics
Summary The least squares principle is applied to the problem of estimating missing points in a time series represented by a Box‐Jenkins seasonal model. The procedure developed is used to estimate the effect of one‐day national holidays on hourly electricity demand. This is done by interpolating over the holiday period using unaffected demand observations from both before and after this period. The ratio of the actual demand to the estimated normal demand, recorded for the same holiday period over successive years, may then be used to forecast the effect on demand of future holidays.