similar to: SSPIR problem

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_eta where the state variable theta has dimension 1(p=1) and at

I'm currently running into a little trouble with the kfilter method, and would love 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),

Hello, I apologize for such a basic question, but I have been trying to do this in multiple packages without much success. I am trying to set up a state space model for Kalman filtering. I am using package dlm. The DLM is specified by: observation: y(t) = F(t)*theta(t) + v(t) state: theta(t) = G(t)*theta(t-1) + w(t) I have no problem setting up a simple example where F is constant. I am

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)

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)?

Please I am new to R. I got the following code from a friend:   gmat <- cbind(gmat,p*(1-p)*wxb) for (j in seq(1:ncol(gmat))) {   gmat[,j] <- fitted(lm(gmat[,j]~zmat)) }   It is for spatial logit.   After defining all the matrices in it such as P, wxb, gmat, and zmat, I tried to run it in R and got the following error message: Error in model.frame.default(formula = gmat[, j] ~ zmat,

Dear list members, Where can I find code for computing the p*p variance-covariance matrix given a vector of p variances (ordered varA, varB, ..., varp) and a vector of all possible correlations (ordered corAB, corAC, ..., corp-1,p)? I know that the covariance between 2 variables is equal to the product of their correlation and their standard deviations: corAB * varA^.5 * varB^.5 and so:

Hi all. I am currently attempting to build a list of sparse matrixes. That I have already achieved, by > vmat <- list() > for (i in 1:n) { > vmat <- c(vmat, sparseMatrix(i,j,x=data) > } How I am trying to select those elements from the list where the column e.g. 999 is not null. I can do this for one of the sparse matrices with > which(vmat[[1]][,999] != 0) which

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:

I am trying to write the following code in R. The code works in S+ and i am trying to do the program in R. x=discrim(admit~gpa+gmat,prior=c("uniform"),data=data.mm) i wrote the following in R: x=lda(admit~gpa+gmat,data=data.mm) i could not figure out how to write prior=c("uniform") in R. I would get an error every time. I think that it has something to do with

Dear list, I would like to plot points with two types of labels, one at the data point (the name of the point) and another offset a bit with another factor which is either of the two greek characters alpha or beta. I have tried to get the routine to plot a greek character with expression() or with substitute() and have not yet had any success. The following only plots the word in english in

Dear R users, I'm using the function coxme of the package coxme in order to build Cox models with complex random effects. Unfortunately, I sometimes get surprising estimations of the variances of the random effects. I ran models with different fixed covariates but always with the same 3 random effects defined by the argument varlist=coxmeMlist(list(mat1,mat2,mat3), rescale = F, pdcheck = F,

Dear R-listers Is there anyone who knows why I get different eigenvectors when I run MatLab and R? I run both programs in Windows Me. Can I make R to produce the same vectors as MatLab? #R Matrix PA9900<-c(11/24 ,10/53 ,0/1 ,0/1 ,29/43 ,1/24 ,27/53 ,0/1 ,0/1 ,13/43 ,14/24 ,178/53 ,146/244 ,17/23 ,15/43 ,2/24 ,4/53 ,0/1 ,2/23 ,2/43 ,4/24 ,58/53 ,26/244 ,0/1 ,5/43) #R-syntax

Hi all, I am working for nest box occupancy data for birds and would like to construct a Markov transition matrix, to derive transition probabilities for ALL years of the study (not separate sets of transition probabilities for each time step). The actual dataset I'm working with is 125 boxes over 14 years that can be occupied by 7 different species, though I have provided a slimmed down

Hey All, I downloaded winebottler so that I can run the GMAT Prep software and was successful in downloading it but i am now running into a few problems. For examples, if there is a "next" icon on the window, I will need to click on it and hit the space bar simultaneously to move on to the next page. I was able to do this on the writing assessment section of the practice test but on the

dear R experts: ?I am writing my own little newey-west standard error function, with heteroskedasticity and arbitrary x period autocorrelation corrections. ?including my function in this post here may help others searching for something similar. it is working quite well, except on occasion, it complains that Error in solve.default(crossprod(x.na.omitted, x.na.omitted)) : system is

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? -

A copy of this question can be found on Cross Validated: https://stats.stackexchange.com/questions/645362 I am estimating a system of seemingly unrelated regressions (SUR) in R. Each of the equations has one unique regressor and one common regressor. I am using `gmm::sysGmm` and am experimenting with different weighting matrices. I get the same results (point estimates, standard errors and

I am having a problem with optim() using the "L-BFGS-B" method. When I set the lower limit for the third parameter equal to zero I get an error message: > low.lim.3 <- 0 > phi_opt <- optim(phi_, model_lik, NULL, method = "L-BFGS-B", lower=c(0.2, -100, low.lim.3, 0), upper= c(10, 100, 10, 10), control = list(maxit = 1000, parscale = c(0.2, u1, 0.002, 0.002), trace =

Generally speaking, this sort of detailed statistical question about a speccial package in R does not get a reply on this general R programming help list. Instead, I suggest you either email the maintainer (found by ?maintainer) or ask a question on a relevant R task view, such as https://cran.r-project.org/web/views/Econometrics.html . (or any other that you judge to be more appropriate).