similar to: comparing ARIMA model to data

hi, i am sure that this is a trivial question but i have not been able to find an answer by searching the mailing lists. i want to plot points on a graph, joined by lines. the command that i am using is points(x, y, type = "b", pch = 21) this plots nice open circles at the data points and draws lines between them. however, the lines do not come all the way up to the edge of the

hello, i have been using ccf() to look at the correlation between lightning and electrogamnetic data. for the most part it has worked exactly as expected. however, i have come across something that puzzles me a bit: > x <- c(1, 0, 1, 0, 1, 0) > y <- c(0, 0, 0, 0, 0, 0) > ccf(x, x, plot = FALSE) Autocorrelations of series 'X', by lag -4 -3 -2 -1 0

hi, i am trying to figure out how to put a caption on the colour scale of a levelplot. there does not seem to be an option for this in levelplot(). i tried using mtext() but as soon as you put the text far out enough on the right of the plot, it goes beyond the plot boundary. so i tried to extend the margin on the right of the plot using par(mar) but this did not have any effect on the plot area.

hello, i have a couple of .R files distributed about my file system. i commonly source() these from other files, but i have to include the full file path. this is not always convenient if you move files around. is there a way of setting the search path for source()? thanks a lot! cheers, andrew. -- Andrew B. Collier Space Physics Group Hermanus Magnetic Observatory Honorary Research Fellow

Dear All, I have a model to predict time series data for example: data(LakeHuron) Lake.fit <- arima(LakeHuron,order=c(1,0,1)) then the function predict() can be used for predicting future data with the model: LakeH.pred <- predict(Lake.fit,n.ahead=5) I can see the result LakeH.pred$pred and LakeH.pred$se but I did not see residual in predict function. If I have a model: [\ Z_t =

According to Hadley's ggplot book (p. 109), both the graphs below should have a legend, and yet none appears in my hands. Any suggestions? I can't see a typo. Is there a bug? library(ggplot2) data(LakeHuron) huron = data.frame(year=1875:1972,level=LakeHuron) p = ggplot(huron, aes(year)) + geom_line(aes(y= level - 5), colour = 'blue') + geom_line(aes(y= level + 5), colour

Hello All, I am trying to create a legend for a black-white graph. The package I use is ggplot2. It can add colors to the legend key but not line types. Can you please help? # example from Wickman (2009, ggplot2 - elegant graphics for data analysis, page 109) library(ggplot2) huron <- data.frame(year=1875:1972, level=LakeHuron) ggplot(huron, aes(year)) +

hello, i have a problem with the orientation of eps files produced with the postscript() command. i have generated some eps files with R using: postscript(file = filename, horizontal = FALSE, paper = "special", onefile = F ALSE, height = height, width = width, pointsize = pointsize) now, when i include these eps files into a standard paper document (ie. a4 paper, portrait orientation)

Dear R-list, I would like to show the implications of estimating a linear trend to time series, which contain significant serial correlation. I want to demonstrate this, comparing lm() and an gls() fits, using the LakeHuron data set, available in R. Now in my particular case I would like to draw confidence bands on the plot and show that there are differences. Unfortunately, I do not know how to

I've posted this before but have not been able to locate what I'm doing wrong. I cannot determine how the forecast is made using the estimated coefficients from a simple AR(2) model when there is an exogenous variable. Does anyone know what the problem is? The help file for arima doesn't show the model with any exogenous variables. I haven't been able to locate any documents

Good afternoon! I'm trying to learn time series but i have a bit of of a problem using R packages for this. 1. > LakeHuron > sample(500:600, 98) > sample(500:600, 98)->t > fit<-arima(LakeHuron, order=c(2,1,1), xreg=t) > fit > predict(fit, n.ahead=1, newxreg=t) Now, my problem is this: is it ok to use the same t in predict function or should my newxreg contain 99

Zulu time will (necessarily) be reckoned relative to Durban, South Africa (capital of KwaZulu-Natal province, South Africa) where the Zulu people live. Brian Brunner brian.t.brunner at gai-tronics.com (610)796-5838 >>> sam at wa4phy.net 11/07/05 07:37PM >>> Peter Farrow wrote: > For those of us who live the promised land where GMT is absolute time > all the this

Dear all I was looking at the aov documentation page and came across the following which seems like a contradiction to me: " This provides a wrapper to |lm| for fitting linear models to balanced or unbalanced experimental designs." (I presume 'This' refers to aov) and "|aov| is designed for balanced designs, and the results can be hard to interpret without

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':

Hi, Could anyone inform how to perform multi-variate auto regression using the past 't' values for regression in R. I have looked at ARMA provided by DES library and mvr provided by PLS library but could not match them to my requirements. Specifically, I want the following Say I have attributes a1-a4. and the regression equation is as follows: a4(t) =

I would like to do the Durban-Watson test on a time series of log returns. 2 questions: 1) If I am just trying to find out if there is serial correlation, what do I do for the residuals? there is no model, so do I just use the log returns (time series) itself? 2) what is the code in R to accomplish this? Regards [[alternative HTML version deleted]]

Hi R users, I use plot.circular(rad, stack=T,bins=4) and could just obtain the four stacks in the directions of 45, 135, 225 and 315 degrees. But I want them in 0, 90, 180 and 270 degrees. Is there any parameter or any other function to make it? Thanks for helping a R beginner. -- Xiaohua Dai, Dr. -------------------------------------------------------------------------------- Centre for

Hallo, "BUON ANNO" "JOYEUX NOEL" "VESELE VANOCE" "MELE KALIKIMAKA" "NODLAG SONA DHUIT" "BLWYDDYN NEWYDD

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This is slightly off-topic but I would be interested in whether anyone has succeeded in creating a filter expression for Google's gmail system that will select messages sent through the R-help and R-devel lists. It seems as if it should be easy to select on '[R]' or '[Rd]' in the subject line but I haven't been able to work out the exact syntax that would do this and not