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...able() to read the entire data. Please help me on how to perform the required computation. I am obviously a new user of this statistical software. Thank you so much for helping. Christabel Jane P. Rubio M.S. Student Water Resources Engineering Dept. of Construction & Environmental Engineering Kongju National University (Cheonan Campus) 102th Office,The 5th Engineering Building, 275, Budae-dong, Cheonan-si, Chungnam-do, 330-717, Korea TEL : +82-41-521-9316 FAX : +82-41-568-0287

i have a loop which looks likes this: > data.info <- rbind(data.info, cbind(station.id, year, date, > max.discharge)) + y <- split(data.info, data.info[station.id]) + for (i in names(y)) {write.csv(y[[i]], file=paste(i, ".csv", sep=","))} i am wondering, where the file (which i am about to write in .csv format) will be saved? i looked at ?write.csv and

i have the following constructed and running very well,, thanks to Gabor Grothendieck for his help. >data.info <- c("station.id", "year", "date", "max.discharge") > > for(i in 1:num.files) { + station.id <- substring(data[i], 1,8) + DF <- read.table(data[i], sep=",", blank.lines.skip = TRUE) + z <- zoo(DF[,4],

hi everyone! hope you can help me here. i am a new R user. what i am trying to do is to find the maximum annual discharge from a daily record. i have a data.frame which includes date and the discharge. somewhat like this.. 10/1/1989 2410 10/2/1989 2460 10/3/1989 2890 ... ... ... 12/31/2005 5730 i have been browsing through the archives and fount out about the aggregate

hi everyone! i want to check the autocorrelation function for a univariate time series (streamflow) in a data frame as below: < DF <- read.table("D:/file path....") < DF year jan feb mar apr ...... dec 1966 0.504 0.406 0.740 0.241 0.429 1967 0.683 0.529 0.780 0.443 0.503 . . . . what i first tried is: acf (DF, plot = TRUE)

hi everyone! I have a 40-year monthy streamflow record. And i want to fit a neural network. I already fitted an autoregressive model and found out that an AR(3) model fits my time series (time.series) the best. I am currently having problems on how to express the argument "formula" for my neural network.. I am aware that my model should be Q(t) ~ Q(t-1) + Q(t-2) + Q(t-3). But I

good day everyone! i have a time series (andong.ts) and fitted and AR() model using the following code andong.ts <- ts(read.table("D:/.../andong.csv", header = TRUE), start = c(1966,1), frequency = 1) ar(andong.ts) Call: ar(x = andong) Coefficients: 1 2 3 0.3117 0.0607 0.0999 Order selected 3 sigma^2 estimated as 0.8443 I am aware that my model is now

hi everyone! season's greetings! is there any way that i can create a normal qqplot showing, aside from the qqline, the 95% confidence limits? thank you very much.. happy holidays! -- View this message in context: http://n4.nabble.com/how-to-create-normal-qqplot-with-the-95-confidence-interval-tp977727p977727.html Sent from the R help mailing list archive at Nabble.com.