similar to: monthplot () - axis change color

Dear colleagues, Can anyone of you tell me how to write a "nabla" symbol in an R graph? Thanks in advance, Nuno ______________________________________________ Centro de Oceanografia - IO-FCUL, Portugal Center for Quantitative Fisheries Ecology - ODU, USA [[alternative HTML version deleted]]

Dear colleagues, I am new to R and statistics so please keep that in mind. I have doubts on the df calculation of Ljung-Box test (Box.test). The function seems to use always the df=lag=m and not df=m-p-q like suggested in Ljung and Box (1978) paper (that is referenced). Do you agree with this? If so, is there an R package function that computes Ljung-Box test with the degrees of

Can someone explain me this spec.pgram effect? Code: period.6<-c(0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10 ,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10,0,0,0,0,0,10) period.5<-c(0,0,0,0,0,10,0,0,0,0,10,0,0,0,0,0,0,10,0,0,0,0,10,0,0,0,0,0,0,10 ,0,0,0,0,10,0,0,0,0,0,0,10,0,0,0,0,10,0,0,0,0,0,0,10,0,0,0,0,10,0) par(mfrow=c(2,1))

Dear R colleagues, This seems pretty straight forward but I have been banging my head on this for some time and can't seem to find a solution suppose I have something like a1<-1; a2<-2; a3<-3; a4<-4; b1<-3; b2<-4 I would like to quickly assign to objects with a certain pattern, e.g., those in ls(pattern="a") a specific value, e.g., "99", without

Dear colleagues, ?arima? returns directly the 1-step ahead errors but I am interested in obtaining other h-step ahead errors for several ARIMA models I have fitted. Is there any way I can obtain this with R? Any help would be appreciated. Sincerely, Nuno Prista _________________________ CO - FCUL, Lisboa, Portugal CQFE - ODU, Norfolk, USA

The monthplot function in S is useful for plotting seasonal data. It's not in base R or the ts package; is it in one of the contributed packages? (I've written a quick version for myself; if there isn't one generally available already, I'll make it public somehow.) Duncan Murdoch -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list

Dear colleagues, I am relatively new to R and time series and so I am experiencing difficulties in interpreting the output of "arima" in MA models (but not in AR models). I cannot make sense of the 1st innovations returned by "arima". In an AR(1) model I expect data[t]=phi1*data[t-1]+a[t] and in a MA(1) model data[t]=a[t]+theta1*a[t-1]. My interpretation from R-help is

Hi all, I would like to adjust the monthplot() of an stl() so that for a time-series with freq=12 (months): a) the curve on the panel for the k-th month graphs the seasonal values minus their monthly mean values b) add to the fig. the values of the k-th month of the seasonal + remainder, also minus their monthly mean values which corresponds to the 'seasonal diagnostic plot as described by

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]]

Dear R help, I'm working with regular 8-daily time-series from 2000 up till now and would like to be able to compare years with each other. E.g. by creating a monthplot via the result of the stl() method it looks ok> but I was wondering whether there exist other methods to plot the different years as lines on top of each other such that years can be compared with each other (temporal

Dear R-users I have some doubts about with converting dates... e.g. dates data 23/12/1975 0.8678 03/01/1976 0.8736 28/01/1976 0.765 13/03/1976 0,9654 ... I think that converting these dates can easily my plots... is there a R function to convert these dates to a julian dates and so plot that variables?? The help files as.POSIXlt, POSIXt and others don't aswer my doubts...

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

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?

Dear Mr. and Mrs. I'm very grateful for these software and this list. My question is: when a use linear multiple regression (lm()) for my data, abundance ichthyoplankton ~ salinity + temperature + month of the year(f1 is a factor: 1 for january, 2 for february, ..., 12 for december), the summary() of results is ... Coefficients: Estimate Std. Error t value Pr(>|t|)

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)

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 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

Hello everyone, I'm doing some benchmark comparing Arima [1] and SVR on time series data. I'm using an out-of-sample one-step-ahead prediction from Arima using the "fitted" method [2]. Do someone know how to have a two-steps-ahead forecast timeseries from Arima? Thanks, Matteo Bertini [1] http://robjhyndman.com/software/forecast [2] AirPassengers example on page 5

Hi, I am far from experienced in both R and time series hence the question. The code for spec.pgram() seems to involve a circularity of the kernel (see below) yielding new power estimates to all frequencies computed by FFT. " if (!is.null(kernel)) { for (i in 1:ncol(x)) for (j in 1:ncol(x)) pgram[, i, j] <- kernapply(pgram[, i, j], kernel, circular = TRUE)