42,95 €
42,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
21 °P sammeln
42,95 €
42,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
21 °P sammeln
Als Download kaufen
42,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
21 °P sammeln
Jetzt verschenken
42,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
21 °P sammeln
  • Format: ePub

The book provides the foundation of time series methods, including linear filters and a geometric approach to prediction. The important paradigm of ARMA models is studied in-depth , as well as frequency domain methods. Entropy and other information theoretic notions are introduced, with applications to time series modeling.

  • Geräte: eReader
  • ohne Kopierschutz
  • eBook Hilfe
  • Größe: 32.05MB
Produktbeschreibung
The book provides the foundation of time series methods, including linear filters and a geometric approach to prediction. The important paradigm of ARMA models is studied in-depth, as well as frequency domain methods. Entropy and other information theoretic notions are introduced, with applications to time series modeling.


Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Tucker S. McElroy is Senior Time Series Mathematical Statistician at the U.S. Census Bureau, where he has contributed to developing time series research and software for the last 15 years. He has published more than 80 papers and is a recipient of the Arthur S. Flemming award (2011).

Dimitris N. Politis is Distinguished Professor of Mathematics at the University of California at San Diego, where he is also serving as Associate Director of the Halicioglu Data Science Institute. He has co-authored two research monographs and more than 100 journal papers. He is a recipient of the Tjalling C. Koopmans Econometric Theory Prize (2009-2011) and is Co-Editor of the Journal of Time Series Analysis.