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The statistical effects of incomplete sampling of coherent data series
Author(s) -
Parker D. E.
Publication year - 1984
Publication title -
journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0196-1748
DOI - 10.1002/joc.3370040409
Subject(s) - autocorrelation , series (stratigraphy) , sampling (signal processing) , statistics , coherence (philosophical gambling strategy) , randomness , mathematics , time series , partial autocorrelation function , expression (computer science) , sampling distribution , computer science , paleontology , filter (signal processing) , autoregressive integrated moving average , computer vision , biology , programming language
An expression is derived for the equivalent number of independent values obtained by partial sampling of a coherent, i.e. autocorrelated, time‐series or spatial series of data. The expression is a function of both the coherence of the data values and the coherence of the sampling, i.e. the non‐randomness of the distribution of available data. For a data series with high autocorrelation the distribution of the sampling in time or space is more important than for a relatively incoherent data series. Meteorological data are used as illustrative examples. The derived expression can be used in estimating the variance of sample means.