Displaying 20 results from an estimated 7000 matches similar to: "kalman"
2001 Sep 10
5
?? hmm ??
Hello again!
thanks to all who helped with overlay plots - v. easy in the end.
Anyway, another new(ba)bee type question - the gurus will cringe I'm sure!
Q. simple R function
mm <- function (u) {
x <- u$GDP
x
m <- mean(x)
m
}
When the function is called the vector "x" does not get printed from within
the function, but the mean value "m" does, why?
I
2001 Sep 06
2
overlay plots
Hi all!
I new to R (I don't know anything about S+ either!)
I've a simple question:
How do I generate overlay plots in R?
So far as I can see the plot(x, y) operator will only give me one graph and
the plot(x ~ y + z) will give me 2 separate plots.
Is there an easy way to overlay or am I missing the obvious?
Any help welcome.
Gerard Keogh
The information in this email, and any
2001 Dec 16
3
Arima
I did a regression with ARMA errors using arima0 with
ari<-arima0(y,order=c(2,0,2),xreg=reg1,delta=-1)
or
ari<-arima0(y,order=c(2,0,2),xreg=reg1)
where reg1 is the matrix of the regressors and when I see diag(ari$var.coef)
I get negative terms. Do you know what this mean ?
I try to change transform.pars to 0 or 1 but this crash R on Windows.
Is it possible to test the significativity
2006 Dec 20
2
Kalman Filter in Control situation.
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
2008 Feb 26
2
Kalman Filter
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?
2000 Nov 08
3
state-space models and kalman filter
Hello again,
A different but related question to my last one:
Does anyone know if one can easily estimate state-space models
using ML and the kalman filter using R? I would be especially
interested in a relatively flexible function that would allow for
estimation
of hyperparameters, or could be made to do so.
Thanks
Michael J. Roberts
Resource Economics Division, PMT
USDA-ERS
202-654-5557
2006 Jan 03
2
KALMAN FILTER HELP
Hi All,
Currently I'm using DSE package for Kalman Filtering. I have a dataset
of one dependent variable and seven other independent variables. I'm
confused at one point. How to declare the input-output series using
TSdata command. Because the given example at page 37 showing some error.
rain <- matrix(rnorm(86*17), 86,17)
radar <- matrix(rnorm(86*5), 86,5)
mydata <-
2007 Nov 15
3
kalman filter estimation
Hi,
Following convention below:
y(t) = Ax(t)+Bu(t)+eps(t) # observation eq
x(t) = Cx(t-1)+Du(t)+eta(t) # state eq
I modified the following routine (which I copied from: http://www.stat.pitt.edu/stoffer/tsa2/Rcode/Kall.R) to accommodate u(t), an exogenous input to the system.
for (i in 2:N){
xp[[i]]=C%*%xf[[i-1]]
Pp[[i]]=C%*%Pf[[i-1]]%*%t(C)+Q
siginv=A[[i]]%*%Pp[[i]]%*%t(A[[i]])+R
2010 May 25
2
Kalman Filter
Hello
My name is greigiano am student of Applied Economics, Department of Rural
Economy.
I am working on an article forecasting, which use the dynamic linear model,
a model state space. I am wondering all the commands in R, to represent the
linear dynamic model and Kalman filter.
I am available for any questions.
--
DEUS Seja Louvado
Que ELE Ilumine sua vida
Assim como ELE tem Iluminado a Minha
2010 Nov 14
5
kalman filter
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?
-
2009 May 10
1
Help with kalman-filterd betas using the dlm package
Hi all R gurus out there,
Im a kind of newbie to kalman-filters after some research I have found that
the dlm package is the easiest to start with. So be patient if some of my
questions are too basic.
I would like to set up a beta estimation between an asset and a market index
using a kalman-filter. Much littarture says it gives superior estimates
compared to OLS estimates. So I would like to
2001 Oct 04
2
about the char _
Dear all,
I don't know the historical reason why the char '_' was
defined in the R language grammar as a synonyme of the
assignment <-, anyway the R documentation dosen't recommand
its usage.
Well, this is a real "incompatibility issue" each time
we need to interface R with other language/systems, notably with
database systems. Recall that, in perhaps all
2005 Dec 14
1
Kalman Filter Forecast using 'SSPIR'
Dear R Users,
I am new to state-space modeling. I am using SSPIR
package for Kalman Filter. I have a data set containing one dependent
variable and 7 independent variables with 250 data points. I want to use
Kalman Filter for forecast the future values of the dependent variable
using a multiple regression framework. I have used ssm function to
produce the state space (SS)
2009 Sep 11
3
State Space models in R
Hello everybody,
I am writing a review paper about State Space models in R, and I would
like to cover as many packages as I reasonably can.
So far I am familiar with the following tools to deal with SS models:
* StructTS, Kalman* (in stats)
* packages dse[1-2]
* package sspir
* package dlm
I would like to have some input from users who work with SS models:
are there any other packages for SS
2008 Oct 31
1
Kalman Filter
Hi,
I am studying Kalman Filter and it seems to be difficult for me to apply the
filter on a simple ARMA.
It is easy to construct the state-space model, for instance:
dlmModARMA(ar=c(0.4,-0.2),ma=c(0.2,-0.1, sigma2=1)
but applying the dlmFilter on it, it doesn't work...
I don't know if my problem is clear but if anyone has already worked on
Kalman filter, it could be great to advise me!
2011 Sep 17
1
£50 for help in my masters dissertation kalman filter forecasting
Dear R users,
Just to clarify. I am not offering to pay someone to do my Dissertation.
These 4-5 commands on Kalman Filter would be only a tiny part of my 10,000
words dissertation. A part that even after trying for a few days, I am still
stuck on. I am offering ?50, just to say thanks.
Regards
--
View this message in context:
2006 Mar 29
1
Data assimilation / inverse modeling in R
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
2010 Aug 13
2
Kalman filter
Dear All,
Could anyone?give me a hand?to suggest few packages in R to running Kalman
prediction and filtration ?
Thanks
Fir
2009 Aug 19
1
New package for multivariate Kalman filtering, smoothing, simulation and forecasting
Dear all,
I am pleased to announce the CRAN release of a new package called 'KFAS' -
Kalman filter and smoother.
The package KFAS contains functions of multivariate Kalman filter,
smoother, simulation smoother and forecasting. It uses univariate approach
algorithm (aka sequential processing), which is faster than normal method,
and it also allows mean square prediction error matrix Ft to
2009 Aug 19
1
New package for multivariate Kalman filtering, smoothing, simulation and forecasting
Dear all,
I am pleased to announce the CRAN release of a new package called 'KFAS' -
Kalman filter and smoother.
The package KFAS contains functions of multivariate Kalman filter,
smoother, simulation smoother and forecasting. It uses univariate approach
algorithm (aka sequential processing), which is faster than normal method,
and it also allows mean square prediction error matrix Ft to