similar to: One last thing

To whomever it may concern, I'm a young Industrial Engineer working on Senior Design at Georgia Tech and have found the StructTS method to be excellent for the training set for my forecasting project. There's only one problem: I don't actually understand what a Structural Time Series IS. I've looked up resources on it, and get that essentially you're dividing the Time

1. The function "KalmanLike" seems to change its inputs AND PREVIOUSLY MADE copies of the inputs. Consider the following (using R 2.1.0 patched under Windows XP): > Fig2.1 <- StructTS(x=Nile, type="level") > unlist(Fig2.1$model0[2:3]) a P 1120 286379470 > tst2 <- tst <- Fig2.1$model0 > tst23 <- tst[2:3] > tst23u <-

I familarized myelf with kalmanlike and structts which are approaches for building and estimating ( and forecasting ) state space models ( or the equivalent arima models ). back in 2003, gavin simpson wrote an email describing the west and harrison apprach to estimate state space models and asked if anything was out there for using that approach. the goals of this approach are the same as kalman

Hi My name is Vladimir Samaj. I am a student of Univerzity of Zilina. I am trying to implement Kalman Filter into my school work. I have some problems with understanding of R version of Kalman Filter in package stats( functions KalmanLike, KalmanRun, KalmanSmooth,KalmanForecast). 1) Can you tell me how are you seting the initial values of state vector in Kalman Filter? Are you using some method?

Dear all: I want to modify the 'StructTS' function from the 'stats' package. First, I am writing a working copy of the original version and got some problems. I have two versions of the function plus the original one. The first version is the same code as the 'StructTS' function: StructTS.v1 <- function (x, type = c("level", "trend",

>From the help document on KalmanLike, KalmanRun, etc., I see the linear Gaussian state space model is a <- T a + R e y = Z' a + eta following the book of Durbin and Koopman. In practice, it is useful to run Kalman filtering/smoothing/forecasting with exogenous factor: a <- T a + L b + R e y = Z' a + M b + eta where b is some known vector (a function of time). Some other

I apologize in advance if I picked the wrong list to post this to. I have made an effort to find the answers to these questions on CRAN, but if they are there, I couldn't find them, and I was going to email the developer of StructTS directly but could not find who that is. I have 2 interrelated questions about StructTS 1. Where can I obtain the source code for StructTS if I wanted to

Hi all, I've experienced this problem using StructTS(x) when the *first* element of x is a NA (R:R1.7.0, os: w2ksp4). Please look at the following code: a=rep(1:7,10) library(ts) #this works StructTS(a) #this works x=a x[2]=NA StructTS(x) #this doesn't work x=a x[1]=NA StructTS(x) The last command returns this error "Error in optim(init[mask], getLike,

I've just built R 2.9.2 from source on Slackware Linux 13.0 - 32-bit (will try 64-bit also next) - and seen: > Collecting examples for package 'stats' > Running examples in package 'stats' > Error: testing 'stats' failed > Execution halted > make[3]: *** [test-Examples-Base] Error 1 Looking at R-2.9.2/tests/Examples/stats-Ex.Rout.fail I see: ... >

Dear All, I am trying to fit a structural time series model using the StructTS function (package stats) with only 2 seasons (summer and winter). More than 2 seasons work fine but with 2 seasons I get this error: > fit <- StructTS(y.ts, type="BSM") Error in T[cbind(ind + 1L, ind)] <- 1 : subscript out of bounds I have looked at Prof. Ripley's 2002 RNews article but cannot

>From: "Ivaha C (AT)" <civaha at glam.ac.uk> >Date: 2008/04/10 Thu AM 08:51:14 CDT >To: R Help <r-help at r-project.org> >Subject: [R] Structural Modelling in R-project if you have a univariate time series and you want to break it into its various components, then you get the scalars based on a decomposition. if you have a kalman filter/ basic strucutural

Dear R-bugs I have been studying the StructTS function (in package 'stats') and functions supplied with it. I think I have found a few minor bugs in the documentation. I am referring to the version of StructTS supplied with the release R 2.0.0. Output from 'version' platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status

Dear all, I'd like to discuss about a possible bug in function StructTS of stats package. It seems that the function returns wrong value of the log-likelihood, as the added constant to the relevant part of the log-likelihood is misspecified. Here is an simple example: > data(Nile) > fit <- StructTS(Nile, type = "level") > fit$loglik [1] -367.5194 When computing the

Hi everybody, I'am very interested with the basic structural model of time series. So I used the command "StructTS" but I failed to obtain a desirable output, in fact when I write in R Console the following lines: > x=(1,2,3,4,5,2,25,14,12,13,11,6,9,24,12,13,14,12,12,14,11,12,14,15,20,21,22,23,21,25,28) >(fit <- StructTS(x,type = "BSM")) I obtained the following

Hello, I just ran the predict.StructTS function using the AirPassengers data and got a ridiculous result. Here's what I ended up with: http://24.210.155.111/PredictWhat!.pdf Who wrote this? Am I seriously supposed to think this function would accurately predict a time series? -AnalogKid

Hello, I would like use Kalman filter for estimating parameters of a stochastic model. I have developed the state space model but I don’t know the correct way use Kalman filter for parameter estimation. Has anybody experience in work with Kalman filter in R. I don’t know the correct function. Maybe it is - KalmanLike; but what is the correct Input? - tsmooth? -

In the examples for StructTS -- ($RHOME)/library/stats/man/StructTS.Rd -- could par(mfrow = c(4, 1)) plot(log10(UKgas)) plot(cbind(fitted(fit), resids=resid(fit)), main = "UK gas consumption") become plot(log10(UKgas)) par(mfrow = c(4, 1)) plot(cbind(fitted(fit), resids=resid(fit)), main = "UK gas consumption") ## Note that par was moved down This makes the plot of UKgas

Dear all, I am applying the StructTS function in ts-package. For some time series the program terminates and the following error appears: Error in optim(init[mask], getLike, method = "L-BFGS-B", lower = rep(0, : L-BFGS-B needs finite values of fn Do someone know what do I have to adjust in the original time series to avoid this error? It works fine for some subsets of the

Hi, I used function StructTS some time ago to fit a structural model to a time series. Now with R 1.6.2-1 I repeated the analysis with the same series and I get the following error: Error in KalmanLike2(y, Z, -1) : invalid argument type I tried with other series and I get the same error; I checked the examples in the documentation and they work fine. I suspect I am missing something

Hello, Does anybody know if (and how) it is possible to obtain standard errors of estimated variances from StructTS? (R 2.10.0). Thank you in advance, Giovanni