Time Series Analysis by Projection. I. Statistical Properties of Fourier Analysis

Astronomy and Astrophysics – Astronomy

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

44

Methods: Analytical

Scientific paper

Most time series analysis methods are equivalent to treating the data as a vector in function space, then projecting the data vector onto a subspace of low dimension. By casting various Fourier methods in terms of projection, we can make their behaviors transparent and adapt them to time series with irregular time spacing. Exact statistics are derived for the discrete Fourier transform, the Lomb-Scargle modified periodogram [Lomb, APSS, 39, 447 (1976); Scargle, APJ, 263, 835 (1982)], and the date-compensated discrete Fourier transform [Ferraz-Mello; AJ, 86, 619 (1981)]. Fourier methods have an extra complication, that they are not merely projections but parametric projections. As a consequence, the standard statistical evaluation of Fourier analysis (and most period-search methods) is incomplete.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Time Series Analysis by Projection. I. Statistical Properties of Fourier Analysis does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Time Series Analysis by Projection. I. Statistical Properties of Fourier Analysis, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Time Series Analysis by Projection. I. Statistical Properties of Fourier Analysis will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-968313

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.