similar to: This is supposed to predict a time series?!

I've just built R 2.9.2 from source on Slackware Linux 13.0 - 32-bit (will try 64-bit also next) - and seen: > Collecting examples for package 'stats' > Running examples in package 'stats' > Error: testing 'stats' failed > Execution halted > make[3]: *** [test-Examples-Base] Error 1 Looking at R-2.9.2/tests/Examples/stats-Ex.Rout.fail I see: ... >

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

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

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 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

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

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

Dear all: I want to modify the 'StructTS' function from the 'stats' package. First, I am writing a working copy of the original version and got some problems. I have two versions of the function plus the original one. The first version is the same code as the 'StructTS' function: StructTS.v1 <- function (x, type = c("level", "trend",

I have seen a couple of posts about this, but no solutions. The problem is fitting the Basic Structural Model (BSM) to the AirPassengers time series using StructTS. ?For this particular time series, if the length is reduced below 140 months, the BSM fits are bad.? The following illustrates the problem ap0 <- log10(AirPassengers) - 2ap<-ts(ap0[1:139], freq=12) ?# bad fits for length <

I am having problems with forward prediction using the output of the Basic Structural Model from StructTS. The following snippet illustrates the problem: t_end <- 139 nahead <- 20 data(AirPassengers) ap <- log10(AirPassengers)-2 fit <- StructTS(ts(ap[1:t_end], freq=12), type="BSM") p <- stats:::predict.StructTS(fit, n.ahead=nahead) plot(1:t_end, ap[1:t_end],

Hi, When I run this code a part of my x-axis and y-axis changes color. Can somebody tell me what is wrong? Also, is there a way to control the color of the average lines? monthplot(AirPassengers+500, ylim=c(min(AirPassengers), max(AirPassengers+500)), ylab="") par(new=T) monthplot(AirPassengers, col="blue", ylim=c(min(AirPassengers), max(AirPassengers+500)),

data(AirPassengers) brings AirPassengers into the workspace. How can I  idenfity what the structure of AirPassengers is? Is it a data.frame, a table etc. etc. [[alternative HTML version deleted]]

Hi, i want to construct a data set similar to "AirPassengers". Its attributes are following. > attributes(AirPassengers) $tsp [1] 1949.000 1960.917 12.000 $class [1] "ts" How Can I construct a data set similar to it having same class and attributes. Thanks -- Amar Kumar Nandan ?:nandan.amar at gmail.com http://aknandan.co.nr

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

Hello, I'm an R newbie. I've tried to search, but my search skills don't seem up to finding what I need. (Maybe I don't know the correct terms?) I need the standard errors and not the confidence intervals from an ARIMA fit. I can get fits: > coef(test) ar1 ma1 intercept time(TempVector) - 1900

Greetings: I'm using the time series decomposition routine "stl" from the package "stats". But how do I get the results into a vector to work with them? example: data(AirPassengers) m<-stl(AirPassengers,"per") print(m) This lists the output but can't figure out how to extract the individual series like seasonal, trend, irregular. Thanks, Bob

Given: data(AirPassengers) I get a ts data structure AirPassengers in the workspace. How can I generate the code that can create that structure? That is, given an example of a data structure, is there a way to generate the code that can greate that structure? Alternatively, is there a reference that provides a list of dta structures together with a full list of theor respective attributes?

Hola usuarios, Necesito detectar si existe o no un cambio de tendencia y si dicho cambio es significativo, para una serie temporal del tipo AirPassengers, en la que a partir de un determinado momento se ha hecho una campaña (supongamos que una promoción de vuelos). Para ello he pensado varios métodos: Usar la descomposición espectral de la muestra [decompose(AirPassengers)] y luego una Regresión

Hello! I have such a problem... Estimated a model based on common data (you can find it in R library), and I wanted to plot the orginal values with the estimated one. Unfortunately I can only see the original values. Below is the code with data library: / library(forecast) data(AirPassengers) AP <- AirPassengers class(AP) start(AP) end(AP) frequency(AP) lgAP <- log(AP) t<-2:length(AP)

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