similar to: Kalman Filter in Control situation.

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)

Hi, I am trying to figure how to use dlm with constant terms (possibly time-dependent) added to both equations y_t = c_t + F_t\theta_t + v_t \theta_t = d_t + G_t\theta_{t-1} + w_t, in the way that S-PLUS Finmetrics does? Is there any straightforward way to transform the above to the default setup? Thanks, Tsvetan -------------------------------------------------------- NOTICE: If received in

Dear all, I am currently trying to use the "dlm" package for Kalman filtering. My model is very simple: Y_t = F'_t Theta_t + v_t Theta_t = G_t Theta_t-1 + w_t v_t ~ N(0,V_t) = N(0,V) w_t ~ N(0,W_t) = N(0,W) Y_ t is a univariate time series (1x1) F_t is a vector of factor returns (Kx1) Theta_t is the state vector (Kx1) G_t is the identity matrix My first

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 this code that would work. Any help will be greatly

Hi All, I'm trying to do a Scatterplot (package: car), and add a line (just for reference). There is my code: #------------------------------------Code--------------------------------------------------- library("car") library("calibrate") G_T<-c("car","bike","boat") ave<-c(80,10,45) perf<-c(100,80,75) df2<-data.frame(G_T,ave,perf)

Dear r-users! I have another question regarding the dlm package and I would be very happy if someone could give me a hint! I am using the dlm package to get estimates for an endogenous rate of capacity utilization over time. The general form of a state space model is (1) b_t = G * b_t-1 + w_t w_t ~ N(0,W) (2) y_t= A' * x_t + H' * b_t + v_t v_t ~ N(0,V) (Hamilton 1984: 372) The

I'm more like a caveman when it comes to programming tools. So, with that in mind, is there a way to use readBin in a batch format to read in pieces of a large binary file? Thank you for the consideration of my question. Todd Remund

I am looking for a fast way to count the number of rows in a matrix are identical to a pattern vector. For example, if I am interested in counting the number of row vectors in a matrix that are identical to (1,2,3) what would I do? I have tried the identical statement in a loop but this is far too slow. I have a very large matrix and need to avoid loops at all costs. Thanks for any help.

I have obtained from transfer functions, the state space matrices for the following state space model. x* = Ax + Bu y = Cx + Du I have A, B, C, and D, now I would like to take the exogenous inputs and simulate the data using the state space model. I know there is a simulate function in the package dse1, but I am unsure as to what type of TSmodel to create to put into it. Could anyone give me

Dear all, I have a serious problem to solve my model. I study over exploitation of fish in the bay of biscay (france). I know only the level of catch and the fishing effort (see data below) by year. My model is composed by the following equations: * the growth function Gt(St) = r*St*(1-St/sbar) with Gt the growth of each period t r intrinsec growth of the stock sbar carriyng capacity of the

Dear R users, suppose we have a random walk such as: v_t+1 = v_t + e_t+1 where e_t is a normal IID noise pocess with mean = m and standard deviation = sd and v_t is the fundamental value of a stock. Now suppose I want a trading strategy to be: x_t+1 = c(v_t – p_t) where c is a costant. I know, from the paper where this equations come from (Farmer and Joshi, The price dynamics of common

Hello, R community, I have been using the lmer and mcmcsamp functions in R with some difficulty. I do not believe this is my code or data, however, because my attempts to use the sample code and 'sleepstudy' data provided with the lme4 packaged (and used on several R-Wiki pages) do not return the same results as those indicated in the help pages. For instance: > sessionInfo() R

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 *

I have had a strange problem with rgl. I am currently switching from a desktop computer to a workstation. When I get a very large data set and run spectro3D, the computations run then the window with the 3d plot appears it doesn't show the data inside and immediately shuts down R. The computers have OpenGL on them, but a colleague suspects the configuration of rgl with OpenGL may be the

I’m ordering a new computer to increase my ability to handle large data sets. I’ve tried the dual core type and also the dual processor with dual cores each, and have not been satisfied. This seems to agree with all the other postings on the help list. I don’t want to do any simulations, I just want to deal with a large data set and do things such as resampling time series data from 50,000

Dear R-help-archive.. I am trying to figure out how to make arima prediction when I have a process involving multivariate time series input, and one output time series (output is to be predicted) .. (thus strictly speaking its an ARMAX process). I know that the arima function of R was not designed to handle multivariate analysis (there is dse but it doesnt handle arma multivariate analysis, only

I'm trying to create a 3D plot using wireframe with certain parts removed. I would like to get rid of the part of the outer cube that crosses over the plot leaving the back two walls and the axes. It would also be useful to put lines in the plot separate from the wireframe call. I've looked through the documentation and have not been able to find such a request. Here is my code

Just out of curiosity, why might this be occuring: > class(x6) [1] "mcmc" > crosscorr.plot(x6) NULL # Replicable code example(lmer) x6 <- mcmcsamp(fm1, n=1000) crosscorr.plot(x6)

I have looked through the documentation and have not been able to find a way of using an xlim, ylim, or zlim type option on rgl.surface. I know that persp3d has the option, but seems to only be able to expand the axes not reduce them. Is there anyone who has an idea of how to do this? Thank you for your time. [[alternative HTML version deleted]]

I know that there is a function, (spectro3D), that produces the Power Spectrogram. Are there R functions that produce the Frequency Spectrogram and the Phase Spectrogram? Thank you for your time. [[alternative HTML version deleted]]