Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-5g6vh Total loading time: 0 Render date: 2024-04-29T17:23:30.353Z Has data issue: false hasContentIssue false

11 - Time series analysis

Published online by Cambridge University Press:  05 November 2012

Eric D. Feigelson
Affiliation:
Pennsylvania State University
G. Jogesh Babu
Affiliation:
Pennsylvania State University
Get access

Summary

The astronomical context

Time-domain astronomy is a newly recognized field devoted to the study of variable phenomena in celestial objects. They arise from three basic causes. First, as is evident from observation of the Sun's surface, the rotation of celestial bodies produces periodic variations in their appearance. This effect can be dramatic in cases such as beamed emission from rapidly rotating neutron stars (pulsars).

Second, as is evident from observation of Solar System planets and moons, celestial bodies move about each other in periodic orbits. Orbital motions cause periodic variations in Doppler shifts and, when eclipses are seen, in brightness. One could say that the birth of modern time series analysis dates back to Tycho Brahe's accurate measurement of planetary positions and Johannes Kepler's nonlinear models of their behavior.

Third, though less evident from naked eye observations, intrinsic variations can occur in the luminous output of various bodies due to pulsations, explosions and ejections, and accretion of gas from the environment. The high-energy X-ray and gamma-ray sky is particularly replete with highly variable sources. Classes of variable objects include flares from magnetically active stars, pulsating stars in the instability strip, accretion variations from cataclysmic variable and X-ray binary systems, explosions seen as supernovae and gamma-ray bursts, accretion variations in active galactic nuclei (e.g. Seyfert galaxies and quasi-stellar objects, quasars and blazars), and the hopeful detection of gravitational wave signals. A significant fraction of all empirical astronomical studies concerns variable phenomena; see the review by Feigelson (1997) and the symposium New Horizons in Time Domain Astronomy (Griffin et al. 2012).

Type
Chapter
Information
Modern Statistical Methods for Astronomy
With R Applications
, pp. 292 - 336
Publisher: Cambridge University Press
Print publication year: 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • Time series analysis
  • Eric D. Feigelson, Pennsylvania State University, G. Jogesh Babu, Pennsylvania State University
  • Book: Modern Statistical Methods for Astronomy
  • Online publication: 05 November 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9781139015653.012
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Time series analysis
  • Eric D. Feigelson, Pennsylvania State University, G. Jogesh Babu, Pennsylvania State University
  • Book: Modern Statistical Methods for Astronomy
  • Online publication: 05 November 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9781139015653.012
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Time series analysis
  • Eric D. Feigelson, Pennsylvania State University, G. Jogesh Babu, Pennsylvania State University
  • Book: Modern Statistical Methods for Astronomy
  • Online publication: 05 November 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9781139015653.012
Available formats
×