similar to: "Error: testing 'stats' failed" - R 2.9.2 on Linux

Hi all, I've experienced this problem using StructTS(x) when the *first* element of x is a NA (R:R1.7.0, os: w2ksp4). Please look at the following code: a=rep(1:7,10) library(ts) #this works StructTS(a) #this works x=a x[2]=NA StructTS(x) #this doesn't work x=a x[1]=NA StructTS(x) The last command returns this error "Error in optim(init[mask], getLike,

In the examples for StructTS -- ($RHOME)/library/stats/man/StructTS.Rd -- could par(mfrow = c(4, 1)) plot(log10(UKgas)) plot(cbind(fitted(fit), resids=resid(fit)), main = "UK gas consumption") become plot(log10(UKgas)) par(mfrow = c(4, 1)) plot(cbind(fitted(fit), resids=resid(fit)), main = "UK gas consumption") ## Note that par was moved down This makes the plot of UKgas

can you recommend a good manual for R that starts with a data set and gives demonstrations on what can be done using R? I downloadedR Langauage definition and An introduction to R but haven't found them overly useful. I'd really like to be able to follow some tutorials using a dataset or many datasets. The datasets I have available on R are Data sets in package 'datasets':

Dear R-bugs I have been studying the StructTS function (in package 'stats') and functions supplied with it. I think I have found a few minor bugs in the documentation. I am referring to the version of StructTS supplied with the release R 2.0.0. Output from 'version' platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status

Dear all, I am applying the StructTS function in ts-package. For some time series the program terminates and the following error appears: Error in optim(init[mask], getLike, method = "L-BFGS-B", lower = rep(0, : L-BFGS-B needs finite values of fn Do someone know what do I have to adjust in the original time series to avoid this error? It works fine for some subsets of the

I have a set of data (in a matrix). I spliced a column out and parsed it as.ts (time series). I then plotted the time series but I found that it was very noisy. I wanted to smooth it out. However, I am having some problems smoothing and plotting the smoothed version. > A <- as.ts(read.table(choose.files())) > x <- as.ts(A[,10]) > plot(x) > > plot(smooth(x))

I apologize in advance if I picked the wrong list to post this to. I have made an effort to find the answers to these questions on CRAN, but if they are there, I couldn't find them, and I was going to email the developer of StructTS directly but could not find who that is. I have 2 interrelated questions about StructTS 1. Where can I obtain the source code for StructTS if I wanted to

Dear All, I am trying to fit a structural time series model using the StructTS function (package stats) with only 2 seasons (summer and winter). More than 2 seasons work fine but with 2 seasons I get this error: > fit <- StructTS(y.ts, type="BSM") Error in T[cbind(ind + 1L, ind)] <- 1 : subscript out of bounds I have looked at Prof. Ripley's 2002 RNews article but cannot

>From: "Ivaha C (AT)" <civaha at glam.ac.uk> >Date: 2008/04/10 Thu AM 08:51:14 CDT >To: R Help <r-help at r-project.org> >Subject: [R] Structural Modelling in R-project if you have a univariate time series and you want to break it into its various components, then you get the scalars based on a decomposition. if you have a kalman filter/ basic strucutural

Dear all, I'd like to discuss about a possible bug in function StructTS of stats package. It seems that the function returns wrong value of the log-likelihood, as the added constant to the relevant part of the log-likelihood is misspecified. Here is an simple example: > data(Nile) > fit <- StructTS(Nile, type = "level") > fit$loglik [1] -367.5194 When computing the

Hi everybody, I'am very interested with the basic structural model of time series. So I used the command "StructTS" but I failed to obtain a desirable output, in fact when I write in R Console the following lines: > x=(1,2,3,4,5,2,25,14,12,13,11,6,9,24,12,13,14,12,12,14,11,12,14,15,20,21,22,23,21,25,28) >(fit <- StructTS(x,type = "BSM")) I obtained the following

Hello, I just ran the predict.StructTS function using the AirPassengers data and got a ridiculous result. Here's what I ended up with: http://24.210.155.111/PredictWhat!.pdf Who wrote this? Am I seriously supposed to think this function would accurately predict a time series? -AnalogKid

Dear R, Thanks for helping me locate the source for the StructTS method from stats, but I've run in to a roadblock in reverse engineering it to locate a formula for its forecasting because it calls some compiled C code, a function called KalmanLike. I've looked through that R library that the StructTS method code was located in and could not find it. Sincerely,

Hi, I used function StructTS some time ago to fit a structural model to a time series. Now with R 1.6.2-1 I repeated the analysis with the same series and I get the following error: Error in KalmanLike2(y, Z, -1) : invalid argument type I tried with other series and I get the same error; I checked the examples in the documentation and they work fine. I suspect I am missing something

Hello, Does anybody know if (and how) it is possible to obtain standard errors of estimated variances from StructTS? (R 2.10.0). Thank you in advance, Giovanni

Dear All I would like to use the StructTS function in the ts library to fit the ' BSM ' model. I have some, probably basics, questions about the model and about the function(s): 1) How can I check the statistical significance of the estimated parameters(variances)? 2) Is there some way to find what component "dominate" the series? 3) Is there a function to produce

To whomever it may concern, I'm a young Industrial Engineer working on Senior Design at Georgia Tech and have found the StructTS method to be excellent for the training set for my forecasting project. There's only one problem: I don't actually understand what a Structural Time Series IS. I've looked up resources on it, and get that essentially you're dividing the Time

Hi everyone. I'm having some troubles with STL function to decompose some data. My issue is that I have monthly data from September 2005 up to August 2010 i. e. 60 observations. I define it in the following way: *u<-read.csv("C:/CELEBREX.csv",header = TRUE) u.ts<-ts(u, start=c(2005,9), frequency=12) * The issue is that when I try to use stl(u.ts, 'per') Then the

Hello, I'm getting the following error message when I try to run 'tsdiag' on what seems to be a valid time series: > tsdiag(small) returns: [Error in tsdiag(small) : no applicable method for "tsdiag"] where small is a little test series where I have isolated this problem (the original has 30-years worth of daily data) When I print it (small), it looks like the

Hi, I've noted that not all `predict' methods are hidden in the namespace: > methods("predict") [1] predict.ar* predict.Arima* [3] predict.arima0* predict.glm [5] predict.HoltWinters* predict.lm [7] predict.loess* predict.mlm [9] predict.nls* predict.poly [11] predict.ppr* predict.prcomp* [13]