search for: sspir

Dear R-brains, I'm rather new to state-space models and would benefit from the extra confidence in using the excellent package sspir. In a one-factor model, If I am trying to do a simple regression where I assume the intercept is constant and the 'Beta' is changing, how do I do that? How do i Initialize the filter (i.e. what is appropriate to set m0, and C0 for the example below)? The model I want is: y = alpha + beta...

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...

I am having a problem with the package SSPIR. The code below illustrates it. I keep getting the message: "Error in y - f : non-conformable arrays." I tried to tweak the code below in many different ways, for example, substituting rbind for cbind, and sometimes I get a different error message, but I could not find a variation of thi...

Dear R-Users, I'm using SSPIR package for a spatio-temporal application. Is it possible to modify the structure of the involved matrixes (Fmat, Gmat, Vmat,Wmat)? I want to create a model like this #y(t)=k*theta(t)+epsilon(t) #theta(t)=h*theta(t-1)+eta(t) #epsilon(t) N(0,V) V=sigma2*I #eta(t) N(0,W) W=sigma2_...

Dear R-Help, I'm trying to learn the sspir package for state space modeling. Has anyone coded a cubic spline smoother (continuous time) in state space format in sspir? The syntax for setting up the various matrices would be really helpful. Best Simon -- Simon D.W. Frost, D.Phil. Assistant Adjunct Professor of Pathology University of Calif...

Greetings, I sent the message below to the developer of the contributed R package "sspir", but have yet to receive any response. I would be very grateful for any advice people have on the matter. Thanks, Mark -------- Original Message -------- Subject: possible bug in sspir? Date: Tue, 19 May 2009 16:08:41 -0700 From: Mark Scheuerell <mark.scheuerell at noaa.gov> To:...

...e some clarification if you are able to offer it. When trying to run kfilter, I've been running into errors that seem to result from having mismatched dimensions. Specifically, the dimension of my observations is 2, while the dimension of the state space is 4. In the filterstep function (file sspir_kfs.R), this causes an error at line 111: e <- y - f. Vector y has dimension 4, while vector f has dimension 2. Here's some sample code: ###################################################################### require(sspir) # getting the hang of the kalman filter x.coords <- c(5,6,5,6,...

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 models that I am missing?, which package do you use and why?, what do you think are advantages/ disadvantages of the package you use? Of course I do have my own preferences (biase...

Hey all, I am trying to work under a State Space form, but I didn't get the help exactly. Have anyone eles used this functions? I was used to work with S-PLUS, but I have some codes I need to adpt. Thanks alot, Bernardo [[alternative HTML version deleted]]

...t$par, "\n") Optimal parameters: 0.3 0.005316 0.001280 0.0006127 > cat("Max likelihood:", -phi_opt$value, "\n\n") Max likelihood: 1035 This does not seem to be happening because the function to be optimized, which is minus the likelihood of a SS object (see package SSPIR) is badly behaved: > model.opt <- model > phi(model.opt) <- phi_opt$par > for(i in seq(0.0001, 0.0015, by = 0.0001)) { + phi(model.opt)[3] <- i + model.f <- kfilter(model.opt) + cat(i, model.f$likelihood, "\n") + } 1e-04 828.8 2e-04 888.2 3e-04 930.5 4e-04 961....

Hi all, I've just started working my way through Mike West and Jeff Harrison's _Bayesian Forecasting and Dynamic Models_, and I was wondering if there were any publically-available packages to handle dynamic linear models, as they describe. I found the "dynlm" package, but either I don't yet understand what's going on or that package uses a different sense of the phrase

...ic > modelling for discrete time survival data'. The same author also publish a > Bayesian version of the algorithm 'dynamic discrete-time duration models'. > > The maintainer of the Survival task view advises me to take a look at > http://cran.r-project.org/web/packages/sspir/index.html > Unfortunately, the pkg implements "only" dynamic GLM. > > That's why I'm asking on this list, if someone knows a package for this > implementation? > > Thanks in advance > > Christophe > > > > PS: the pseudo vignette of the ss...

...bability Distribution Functions and Inverses Random Number Generation Utilities As a start, here are the R packages I know of for time series analysis: dyn: Time Series Regression dynlm: Dynamic Linear Regression GeneTS: Microarray Time Series and Network Analysis its: Irregular Time Series sspir: State Space Models in R tseries: Time series analysis and computational finance urca: Unit root and cointegration tests for time series data uroot: Unit root tests and graphics for seasonal time series I would like to see lists corresponding to other categories of IMSL. Another classification s...

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

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? -

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?

Hello, I am a new R user and I need R code for GLARMA. I will be really thankful if you help me. Yours sincerely,

Hi all, I'm working on a term structure estimation using state-space modeling for 1, 2 and 3 factor models. When I started to read the functions on R, I got to the function ss on the library sspir. From what I understood this function is similar to SsfFit from S-PLUS. But for my models purpose there is something left to be desired. Its formulation follow these equations: *Y_t = F_t^T * theta_t + v_t, v_t ~ N(0,V_t)* *theta_t = G_t * theta_{t-1} + w_t, w_t ~ N(0,W_t)* Actually I wanted to...

Hi, I'm trying to use the kalman filter to estimate the variable drift of a random walk, given that I have a vector of time series data. Anyone have any thoughts on how to do this in R? Thanks, Alex [[alternative HTML version deleted]]