search for: kalmanlik

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 <- ts...

>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 wher...

(re-formulate, re-send, without html) for vector y = c(1,2,3,4,5), H = 0.66 manual calculations using the equations below give a = c(1,1.66,2.55,3.51,4.50). KalmanRun with these parameters gives res$states = (1,1,1,1,1)! for Kalman Filter Durbin/Koopman give at p67 eqs 4.13: v = y - Z a, F = Z P Z' + H, K = T P Z' / F + H, a[t+1] = T a + K v, P[t+1] = T P L'

...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? - kfilter? Thanks for helping. I have ask the same question in the help list “sig-dynamic-models” Best, Thomas [[alternative HTML version deleted]]

...eARIMA(). Example: > s <- 12 > phis <- 0.95 > phi1 <- 0.0001 > phi <- c(phi1,rep(0,s-2),phis,-phi1*phis) > theta <- 0.7 > out <- makeARIMA(phi,theta,NULL) > min(eigen(out$Pn)$value) [1] -19.15890 There are consequences of this "bug" in the functions KalmanLike() and arima(). Indeed, arima() in its default behaviour uses first CSS method to get the initial value for an MLE search through optim. To compute the likelihood, it uses getQ0 at the initialization of the Kalman Filter. It may happen that getQ0 returns a covariance matrix which possesse...

Hi it is possible to see the C code for the KalmanLike and Kalmansmooth functions with R? Otherwise, without using R, how can I get the code? Thank arianna

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? 2) I have fond function StructTS in stats package. I dont understand, how exactly, are you computing(what method are you using) fitted v...

Hi R-Experts, Currently I'm using an univariate time series in which I'm going to apply KalmanLike(),KalmanForecast (),KalmanSmooth(), KalmanRun(). For I use it before makeARIMA () but I don't understand and i don't know to include the seasonal coefficients. Can anyone help me citing a suitable example? Thanks in advance. ------------------------------------------ SUMANTA BASAK....

...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", "BSM"), init = NULL, ??? fixed = NULL, optim.control = NULL) { ??? KalmanLike2 <- function(y, mod, nit = 0) { ??????? x <- .Call(R_KalmanLike, y, mod$Z, mod$a, mod$P, mod$T, ??????????? mod$V, mod$h, mod$Pn, as.integer(nit), FALSE, fast = TRUE) ??????? 0.5 * sum(x)/length(y) ??? } #... #... above and remaining code is the same as the original code in StructTS #... }...

Dear R, Thanks for helping me locate the source for the StructTS method from stats, but I've run in to a roadblock in reverse engineering it to locate a formula for its forecasting because it calls some compiled C code, a function called KalmanLike. I've looked through that R library that the StructTS method code was located in and could not find it. Sincerely, Alexander Fretheim

Can anyone help me about pass by reference of arguments in R functions? I have read about .Alias in base package however it is defunct and there is no replacement for it. Thanks in advance.

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...

help.search("Kalman") says to look at help(KalmanLike, package=ts). Andy -----Original Message----- From: Mohamed A. Kerasha [mailto:mohamed at engr.uconn.edu] Sent: Tuesday, November 19, 2002 9:27 AM To: r-help at stat.math.ethz.ch Subject: [R] Kalman Filter Hi all, Does any one know if there is Kalman Filter code or library in R. Thanks, Moh...

hi, i am looking for c code of kalman filtering please can you help me...thankyou bye... --------------------------------- [[alternative HTML version deleted]]

Hola, Estoy intentando implementar el filtro de Kalman para un modelo de series de tiempo que estoy haciendo, me gustaría saber si alguien me puede colaborar ya que soy principiante en R. Muchas gracias! Cordialmente, JAVIER SANTIAGO PARRA RAMOS INGENIERO DE SISTEMAS [[alternative HTML version deleted]]

Hello, I'm currently trying to find a method to interpolate or smooth data that represent a trajectory in space. For example, I have an ordered (=time) set of (x,y) tuples which constitute a path in a 2D space. Is there a way using R to interpolate between these points in a way similar to spline interpolation so that I get a smooth path in space? Greetings, Dieter -- Dieter Vanderelst

Hi List, I have a time series of 122 values, actualy it is a time series of daily indian monsoon rainfall. now i want to filter this time series for a particular oscilation say 10 to 20days oscilation. i want to find out what amount of variance is explained by this mode. Which package is available in R for this purpose. and how to calculate nquest frequancy of this series. any help is much

Hello, I'm trying to find out if something has been written in R regarding data assimilation and inverse modeling. These searches do not return anything that look like Kalman filter variations (EK, SEEK, ROEK, etc.) help.search("assimilation") help.search("inverse model") Regards, ************************************************** AVIS DE NON-RESPONSABILITE: Ce

Hi, I'm having issues with what I believe is a bug in the MCMCpack's MCMCmetrop1R function. I have code that basically looks like this: posterior.sampler <- function(data, prior.mu){ log.posterior <- function(theta) log.likelihood(data, theta) + log.prior(prior.mu, theta) post.samples <- MCMCmetrop1R(log.posterior, theta.init=prior.mu, burnin=100, mcmc=1000, thin=40,

I am looking for a Kalman filter that can handle a control input. I thought that l.SS was suitable however, I can't get it to work, and wonder if I am not using the right function. What I want is a Kalman filter that accepts exogenous inputs where the input is found using the algebraic Ricatti equation solution to a penalty function. If K is the gain matrix then the exogenous input