TY - JOUR
N2 - When observations are autocorrelated, standard formulae for the estimators of variance, s2, and variance of the mean, s2 (x), are no longer adequate. They should be replaced by suitably defined estimators, s2a and s2a (x), which are unbiased given that the autocorrelation function is known. The formula for s2a was given by Bayley and Hammersley in 1946, this work provides its simple derivation. The quantity named effective number of observations neff is thoroughly discussed. It replaces the real number of observations n when describing the relationship between the variance and variance of the mean, and can be used to express s2a and s2a (x) in a simple manner. The dispersion of both estimators depends on another effective number called the effective degrees of freedom Veff. Most of the formulae discussed in this paper are scattered throughout the literature and not very well known, this work aims to promote their more widespread use. The presented algorithms represent a natural extension of the GUM formulation of type-A uncertainty for the case of autocorrelated observations.
L1 - http://rhis.czasopisma.pan.pl/Content/107037/PDF/Journal10178-VolumeXVII%20Issue1_01%20paper.pdf
L2 - http://rhis.czasopisma.pan.pl/Content/107037
PY - 2010
IS - No 1
DO - 10.2478/v10178-010-0001-0
KW - autocorrelated
KW - time series
KW - estimator
KW - unbiased
KW - variance
KW - effective number of observations
A1 - ZiÄ™ba, Andrzej
PB - Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation
DA - 2010
T1 - Effective Number of Observations and Unbiased Estimators of Variance for Autocorrelated Data - an Overview
UR - http://rhis.czasopisma.pan.pl/dlibra/publication/edition/107037
T2 - Metrology and Measurement Systems
ER -