similar to: KalmanSmooth problem

I am trying to use KalmanSmooth to smooth a time series fitted by arima (and with missing values), but the $smooth component of the output baffles me. Look at the following example: testts <- arima.sim(list(ar=0.9),n=100) testts[6:14] <- NA testmod <- arima(testts, c(1,0,0)) testsmooth <- KalmanSmooth(testts, testmod$model) par(mfrow=c(2,1)) plot(testsmooth$smooth,

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?

On Sat, 03 Apr 2004 21:34:25 -0400, you wrote: >Defining the following: > > set.seed(123) > > kalmanTorture <- function(iter) { > x <- arima.sim(model = list(ar=0.9, ma=0.5),n=150 ) > x[10:20] <- NA > mod <- arima(x, order=c(1,0,1) ) > for (i in 1:iter) { > smooth <- KalmanSmooth(x, mod=mod$model)$smooth > if (any(is.na(smooth)))

Hola! I got problems using an objects returned from arima (in KalmanSmooth(my.ts, ModArima$model), because my.ts showed up to have storage mode "integer" (is.integer(my.ts was TRUE). Should storage.mode() of a ts be allowed to be integer, should ts() someplace say storage.mode(ts.out) <- "double", or maybe inside arima() storage.mode(x) <- "double"

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 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. ------------------------------------------

I have a bunch of clean timeseries data obtained from a sensor and I'd like to apply a Kalman Filter to it to smoothe it out. Through a few days of Googling, reading papers, implementing such a filter in various languages, I finally realised that it may be built into R. So I did a "??kalman" at the R prompt and found that it is indeed there. However, the help page is a tad bare,

I have a set of linear equations and would like to find any feasible solution. A simplex solution works in Case 1 below, but not in Case 2. I would be grateful for any help. Case 1: Find any feasible solution for the set of linear equations: a + b + c = 5 a + b + 0c = 4 0a + b + c = 4 Solution - a feasible (and unique) solution is a=1, b=3, c=1. The following R code

x<-matrix(c(1,0,0,0,1,0,0,0,1),nrow=3) > y<-matrix(c(0,0,0,1,0,0,1,1,0),nrow=3) > z<-matrix(c(0,1,0,0,1,0,1,0,0),nrow=3) > x[z]<-y[z] The resultant matrix x is all zeros except for the last two diagonal cells which are 1's. While y is lower triangualr 0's with the remaining cells all ones. I really don't understand how this deceptively simple looking piece of

Hello, I have the following problem: I have a set of n matrix equations in the form of : [b1] = [A] * [b0] [b2] = [A] * [b1] etc. vertical vectors [b0], [b1], ... are GIVEN. We try to estimate matrix A. As there are many equations (more than cells in matrix A) the system has no solutions. A is transition matrix (stochastic matrix) or markov process, so the sum of each row = 1 and each entry is

The byte pixies have rolled up R-2.14.1.tar.gz (codename "December Snowflakes") at 9:00 this morning. This is a maintenance release; see the list below for details. You can get it from http://cran.r-project.org/src/base/R-2/R-2.14.1.tar.gz or wait for it to be mirrored at a CRAN site nearer to you. Binaries for various platforms will appear in due course. For the R Core Team

The byte pixies have rolled up R-2.14.1.tar.gz (codename "December Snowflakes") at 9:00 this morning. This is a maintenance release; see the list below for details. You can get it from http://cran.r-project.org/src/base/R-2/R-2.14.1.tar.gz or wait for it to be mirrored at a CRAN site nearer to you. Binaries for various platforms will appear in due course. For the R Core Team

I am studying statistics using R and a book "Understandable Statistics", by Brase and Brase. The book has two worked examples for calculating a confidence interval around a predicted value from a linear model. The answers to the two examples in the book differ from those I get from R. The regression line, the standard error, and the predicted value in R and the book all agree for the

I've rolled up R-1.9.0.tgz a short while ago. This is a new version with a number of new features, most notably a substantial reorganization of the standard packages, a major update of the grid package, and the fact that underscore can now be used as a regular character in variable names. See below for further changes. Because of the disturbances at the machine that hosted the CVS archives,

I've rolled up R-1.9.0.tgz a short while ago. This is a new version with a number of new features, most notably a substantial reorganization of the standard packages, a major update of the grid package, and the fact that underscore can now be used as a regular character in variable names. See below for further changes. Because of the disturbances at the machine that hosted the CVS archives,

Hello: I read the archive posting for September 2005, http://syslinux.zytor.com/archives/2005-September/005809.html, where you stated that you have a freedos diskette that allows you to download and run an iso like it was a cd in a drive. I am in need of the ability to have a freedos bootable cd that contains other Linux ISO's that I could mount and boot to. In your experience with