Variance Analysis if Unevenly Spaced Time Series Data
Abstract
We have investigated the effect of uneven data spacing on the computation of sigma(chi) (Tau). Evenly spaced simulated data sets were generated for noises processes ranging from white PM to random walk FM. sigma(chi) (Tau) was then calculated for each noise type. Data were subsequently removed from each simulated data set using typical TWSTFT data patterns to create two unevently spaced sets with average intervals of 2.8 and 3.6 days. Sigma(chi)(Tau) was then calculated for each sparse data set using two different approaches. First, the missing data points were replaced by linear interpolation and sigma(chi)(Tau) calculated from this now full data set. The second approach ignored the fact that the data were unevenly spaced and calculated sigma(chi)(Tau) as if the data were equally spaced with average spacing of 2.8 or 3.6 days. Both approaches have advantages and disadvantages, and techniques are presented for correcting errors caused by uneven data spacing in typical TWSTFT data sets.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1995
- Accession Number
- ADA515742
Entities
People
- Christine Hackman
- Thomas E. Parker
Organizations
- National Institute of Standards and Technology