Skip to main content

Estimating The Spectrum

  • Chapter
Time Series Analysis

Part of the book series: Springer Texts in Statistics ((STS))

  • 257k Accesses

Several alternative methods for constructing reasonable estimators of the spectral density have been proposed and investigated over the years. We will highlight just a few of them that have gained the most acceptance in light of present-day computing power. So-called nonparametric estimation of the spectral density (that is, smoothing of the sample spectral density) assumes very little about the shape of the “true” spectral density. Parametric estimation assumes that an autoregressive model—perhaps of high order—provides an adequate fit to the time series. The estimated spectral density is then based on the theoretical spectral density of the fitted AR model. Some other methods are touched on briefly.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 49.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 99.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

(2008). Estimating The Spectrum. In: Time Series Analysis. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-75959-3_14

Download citation

Publish with us

Policies and ethics