Introduction to Local Level Model and Kalman Filter
Introduction to Local Level Model and Kalman Filter
Introduction to Local Level Model and Kalman Filter
You also want an ePaper? Increase the reach of your titles
YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.
Three exercises (cont.)<br />
2. Derive a <strong>Kalman</strong> filter for the local level model<br />
yt = µt + εt, εt ∼ N(0, σ 2 ε), ∆µt+1 = ηt ∼ N(0, σ 2 η),<br />
with E(εtηt) = σεη = 0 <strong>and</strong> E(εtηs) = 0 for all t, s <strong>and</strong> t = s.<br />
Also discuss the problem of missing obervations in this case.<br />
3. Write Ox program(s) that produce all Figures in Ch 2 of DK<br />
except Fig. 2.4. Data:<br />
http://www.ssfpack.com/dkbook.html
Change language