I analyzed the kalman filter based approaches like mean reverting, random coefficient and random walk. At this point Automatic package is inadequate and need some constraints. I also found Kalman Filter code in Shumway$Stoffer book, but it did not provide the correct optimization. Can you suggest any R codes for kalman filter based approaches? Regards, Serdar -- View this message in context: http://r.789695.n4.nabble.com/State-Space-Kalman-Filter-tp4646615.html Sent from the R help mailing list archive at Nabble.com.
"State Space" + "Kalman Filter "
4 messages · Giovanni Petris, nserdar
Package dlm does it, as well as other contributed packages (KFAS, sspir, dse,...) Best, Giovanni
From: r-help-bounces at r-project.org [r-help-bounces at r-project.org] on behalf of nserdar [snes1982 at hotmail.com]
Sent: Thursday, October 18, 2012 8:40 AM
To: r-help at r-project.org
Subject: [R] "State Space" + "Kalman Filter "
Sent: Thursday, October 18, 2012 8:40 AM
To: r-help at r-project.org
Subject: [R] "State Space" + "Kalman Filter "
I analyzed the kalman filter based approaches like mean reverting, random coefficient and random walk. At this point Automatic package is inadequate and need some constraints. I also found Kalman Filter code in Shumway$Stoffer book, but it did not provide the correct optimization. Can you suggest any R codes for kalman filter based approaches? Regards, Serdar -- View this message in context: http://r.789695.n4.nabble.com/State-Space-Kalman-Filter-tp4646615.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
I know these package but I plan to analyse financial multi factorial data set, and also estimate diffuse initial values for these models. I generated my own code, but I had problem with optim() package problem. I need some constraints and I do not apply it in my code. Do you have any suggestion about these problem? Regards, Ser -- View this message in context: http://r.789695.n4.nabble.com/State-Space-Kalman-Filter-tp4646615p4646673.html Sent from the R help mailing list archive at Nabble.com.
So I do not find example what I expect. I plan to estimate the multi-factor model for Kalman Filter Mean Reverting, Random Walk and Random Coefficient. For example: R(it)= Alpha(it)+ Beta(it)R(mt)+Gamma(it)(R(mt)^2)+delta(it)(R(mt)^3)+ V(it) KF Random walk Alpha(it)= Alpha(it-1)+W(i1t) Beta(it)= Beta(it-1)+W(i2t) Gamma(it)= Gamma(it-1)+W(i3t) Delta(it)= Delta(it-1)+W(i4t) Note: (alphabar= Mean Alpha, Betabar= Mean Beta, Gamma= Mean Gamma, Deltabar= Delta Mean) KF Mean Reverting Alpha(it)= Alphabar(i)+ phi* (Alpha(it-1)-Alphabar(i))+W(i1t) Beta(it)= Betabar(i)+ phi* (Beta(it-1)-Betahabar(i))+W(i2t) Gamma(it)= Gammabar(i)+ phi* (Gamma(it-1)-Gammabar(i))+W(i3t) Delta(it)= Deltabar(i)+ phi* (Delta(it-1)-Deltabar(i))+W(i4t) Kf Random Coefficient Alpha(it)= Alpha bar(i)+ W(i1t) Beta(it)= Beta bar(i)+ W(i2t) Gamma(it)= Gamma bar(i)+W(i3t) Delta(it)= Deltabar(i)+W(i4t) Step 1) Maximize MLE to estimate initial values (etc: Alphabar, ...., Delta bar, Variances of State equation Error, Observation Error,..... etc... ) ( I also use L-BFGS-B methods to optimization but I failed. :( ) Step 2) Apply estimated values from step 1 in Kalman Filter to filtering. Then obtain MSE etc ( I can calculate by myself) Please let me know whether I can follow these steps in DLM package or not. Regards, Ser -- View this message in context: http://r.789695.n4.nabble.com/State-Space-Kalman-Filter-tp4646615p4646675.html Sent from the R help mailing list archive at Nabble.com.