similar to: vetor autoregressions and BVARs

Howdy! I am attempting to convert a date frame with irregular dates into a regular time series, aggregated by date. i have tried using both the 'its' and 'zoo' packages. I have something like times<-c("2003-03-05", "2003-03-05", "2003-05-05" ,"2003-04-07" ,"2003-03-05") aarf<-data.frame(times) aarf$x<-runif(5) what i

Hello, I am trying to import SAS files into R using sas.get() in Hmisc. I am running both SAS and R on a UNIX server. I've pasted my command and ensuing errors below: sas.get(lib="EOG", mem="eog3pub00_1") Error in if (status != 0) { : argument is of length zero In addition: Warning message: In sas.get(lib = "EOG", mem = "eog3pub00_1") :

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

I have a bayesian hierarchical normal regression model, in which the regression coefficients are nested, which I've wrapped into one regression framework, y = X %*% beta + e . I would like to run data through the model in a filter style (kalman filterish), updating regression coefficients at each step new data can be gathered. After the first filter step, I will need to be able to feed

h?, I am preparing undergraduate thesis If you help me this would make me feel good. First I need to analyze effect of Dow Jones Industrial average(DJIA)'s return on Istanbul Stock Exchange(ISE). I want to use Markov-Switching Bayesian Vector Autoregression Models (MSBVAR) that is used to examine the effect of a large economy?s stock exchange movement on a small economy?s stock exchange

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'm beginner in Bayesian methods, I'm reading the documentation about dlm package and kalman filters, I'm looking for a example of transformation of ARIMA in a state space equivalent to use the dlm package and calcualte the hyperparameters. Someone can help me about it?. If it's possible with a arima(1,0,1) example, or more complex model. While I have more examples best for me.

I'm searching a method to estimate the hyper-parameters in arima models. I'm reading about r-inla package, but in the examples section only talk about the AR part of the arima, but i need help about the MA part too. I'm beginner in Bayesian methods, I'm reading the documentation about dlm package and kalman filters, but the computacional cost of inla i think is better, but only

Dear R users, I am using mAr package to fit a Vector autoregressive model to my data. But here I want to put some predetermined values for some elements in coefficient matrix that mAr.est going to estimate. For example if p=3 then I want to put A3[1,3] = 0 and keep rest of the elements of coefficient matrices to be determined by mAr.est. Can anyone please tell me how can I do that? Sincerely

Hi all, I'm looking for R packages that estimate multivariate time-series models or vector-autoregression (VAR) time-series models. Thanks David -- =========================================================================== David Kaplan, Ph.D. Professor Department of Educational Psychology University of Wisconsin - Madison Educational Sciences, Room, 1061 1025 W. Johnson Street Madison,

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 all. Are there any R functions around that do quick logistic regression with a Gaussian prior distribution on the coefficients? I just want posterior mode, not MCMC. (I'm using it as a step within an iterative imputation algorithm.) This isn't hard to do: each step of a glm iteration simply linearizes the derivative of the log-likelihood, and, at this point, essentially no

All R experts, How do I fit a dynamic Random effects model with a binary dependent variable in R Thanks JCM [[alternative HTML version deleted]]

Dear list, according to the documentation of acf{ts} "the partial correlation coefficient is estimated by fitting autoregressive models of successively higher orders up to lag.max. " However, R seems to return the Yule-Walker estimates of the PACF by default. You can check this using c(1:10) as the series: the YW estimates are 0.7000000 and -0.1527035 for lags 1 and 2 . If the PACF

Dear R experts, How to find out the index of minimum or maxmum number in a vetor or data.frame? For example, a= n price 1 50 -2 100 0 200 -1 300 ...... I want to find out the row which the n is the smallest or largestest and extract the price. Thanks Ted -- View this message in context:

Dear all, Can anybody tell me how to export a 3d figure made with the plot3d function? I'm careless about whether it's still interactive or not in another format, as long I can get it out of R. Thanks! Alejandro Gonz?lez Departamento de Biodiversidad y Conservaci?n Real Jard?n Bot?nico Consejo Superior de Investigaciones Cient?ficas Claudio Moyano, 1 28014 Madrid, Spain Tel +0034

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)?

Hello, I found my Rnw file generated strange symbols in pdf file. For instance, on page 4 of the following file, http://cran.r-project.org/web/packages/cts/vignettes/kf.pdf you can see Belcher et~al on line 2, and Figure~1 on line 5. The symbol ~ should not appear in the pdf file although the symbol was in the original Rnw file (something like Figure~\ref{...}, section~\ref{...}). On page 1,

Dear R users, I would like to simulate, for 20000 replications, an autoregressive process: y(t)=0.8*y(t-1)+e(t) where e(t) is i.i.d.(0,sigma*sigma), Thank you in advance ____________________________________________________ Écoutez gratuitement le nouveau single de Noir Désir et découvrez d'autres titres en affinité avec vos goûts musicaux

Hi, Few days ago I posted a question to r-sig-finance, which I thought would be an easy one. To my surprise I have received no replies, which makes me think that it is either harder than I thought, or that it makes no sense. I am reposting the message (with some modifications) on the R-help in a hope to get some leads, suggestions for alternatives, etc. My apologies to those who had seen this on