similar to: Problems with the ts library

Hello all R users I want to calculate this univariate integral: exp(-x)*sum(y^x) respect to x from 0 to 3 where y is a vector y=(2,3,5). In fact, the original y vector has a large number of elements but I propose with 3 elements. I know that I can resolve this problem doing fun <- function(x) exp(-x)*(2^x+3^x+5^x) integrate(fun,0,3) When the y vector has a large number of elements the

Hi there, I have R 0.64.2. I wonder if this R has acf function to calculate autocorrelation? since the help(acf) doesnt seem to be able to help me. thanks, Peppy -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

Time Series functions in R ========================== I think a good basic S-like functionality for library(ts) in base R would include ts class, tsp, is.ts, as.ts plot methods start end window frequency cycle deltat lag diff aggregate filter spectrum, spec.pgram, spec.taper, cumulative periodogram, spec.ar? ar -- at least univariate by Yule-Walker arima -- sim, filter, mle, diag, forecast

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 R lovers! I'd like to know if the 2 blue lines in the graph produced by the function acf in the package ts represents the level for the test of significance of the autocorrelation thanks for help vincent ****************************************************************** The sender's email address has changed to firstname.lastname@ sgcib.com. You may want to update your

(Moved from r-devel to r-bugs) On 3/24/2006 5:03 AM, Antonio, Fabio Di Narzo wrote: > Hi all. > There's a bug in plot.acf, when plotting acf for multivariate time series. > Here a reproducible example: > > X <- rnorm(1000) > Y <- -X + rnorm(1000, sd=0.6) > Z <- cbind(X,Y) > > In > acf(Z) > cross-correlation plot y-axis is limited to 0-1. But: >

Hi, I'm not sure if this is a bug or due to my ignorance of R syntax. I'm using hist() to plot a sample set of data, some sets contain the same value (i.e. 3000, 3000, 3000, 3000). I find that hist() hangs when It gets to sets with a single value. ....help ? ...victor -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list --

Hello I have several replicates (30) of a -- short -- time series (19 obs) and I'd like to estimate the first few lags autocorrelation function. Is there an immediate way of handling multiple realizations when computing the ACF in R? I'm using R-1.4.1 on a Linux Debian box. Thanks in advance claudia ------------------------------------------------------------------------- claudia

Hi, The default value for lag.max in ACF implementation is 10*log10(N) There several publications recommending setting lag.max to: - N/4 (Box and Jenkins, 1970; Chatfield, 1975; Anderson, 1976; Pankratz, 1983; Davis, 1986; etc.) - sqrt(N)+10 (Cryer, 1986) - 20<=N<=40 (Brockwell and Davis) Why R uses 10*log10(N) as a default? Please, give me a reference to a book or article where the

There is now a preliminary version of a time series package in the R-devel snapshots, and we would welcome feedback on it. It is based in part on the packages bats (Martyn Plummer) and tseries (Adrian Trapletti) and in part on code I had or have written. (Thanks for the contributions, Martyn and Adrian!) Some of the existing ts code has been changed, for example to plot multiple time series, so

Hi R specialists, The na.omit.ts() method fails when the time series contains internal NA's. How can these automatically be removed? > spectrum(ts.mNDII, na.action=na.omit) Error in na.omit.ts(as.ts(x)) : time series contains internal NAs How can the na.action be activated correctly? > acf(ts.Lin, type=c("correlation"), na.action=na.omit) Error in na.omit.ts(as.ts(x)) :

I have just put up a new executable as a replacement for the one in rseptbeta.zip there have only been a few changes; mostly to the menu's. I am about to start on a major overhaul including getting survival to work and grabbing the 0.60 version once it's stable. Please let me know about other enhancements you want.... robert

I have just put up a new executable as a replacement for the one in rseptbeta.zip there have only been a few changes; mostly to the menu's. I am about to start on a major overhaul including getting survival to work and grabbing the 0.60 version once it's stable. Please let me know about other enhancements you want.... robert

Hello, what is the meaning of the plots of an acf()-plot, when using a data frame as argument? The result is NOT obvious for me. There are combinations of the columns of a dataframe in the reulting plot. But an acf() is just defined for onyl one time-sreies. So what do the plots mean? I did not found a description in the help-page. Ciao, Oliver

Hi all, I have some residuals from regression, and i suspect they have correlations in them... I am willing to cast the correlation into a ARMA(p, q) framework, what's the best way to identify the most suitable p, and q, and fit ARMA(p, q) model and then correct for the correlations in regression? I know there are functions in R, I have used them before, but I just want to see if I can do

Hi, I don't quite understant how can I access to the acf values from the list produced by the acf function Example: library(ts) t <- acf(ts.union(ts(1:10), ts(11:20))) t$acf > tmp$acf , , 1 [,1] [,2] [1,] 1.00000000 1.00000000 [2,] 0.70000000 0.70000000 [3,] 0.41212121 0.41212121 [4,] 0.14848485 0.14848485 [5,] -0.07878788 -0.07878788 [6,] -0.25757576

I need to modify the graph of the autocorrelation. I tried to do it through plot.acf but with no success. 1. I would like to get rid of the lag zero 2. I would like to have numbers on the x-axis only at lags 12, 24, 36, 48, 60, ... Could anybody help me in this? Any help will be appreciated Thank you for your attention Stefano [[alternative HTML version deleted]]

Hi everyone, I've got a question concerning the function acf(.) in R for calculating the autocorrelation in my data. I have a table with daily returns of several stocks over time and I would like to calculate the autocorrelation for all the series (not only for one time series). How can I do this? After that I want to apply an autoregressive model based on the estimated lag in the

Hi R users, where can I find the equations used by acf function to calculate autocorrelation? I think I misunderstand acf. Doesn't acf use following equation to calculate autocorrelation? [image: R(\tau) = \frac{\operatorname{E}[(X_t - \mu)(X_{t+\tau} - \mu)]}{\sigma^2}\, ,] If it does, then the autocorrelation of a sine function should give a cosine; however, the following code gives a

Hello, I am attending a course in Computational Statistics at ETH and in one of the assignments I am asked to prove that a time series is not autocorrelated using the R function "acf". I tried out the acf function with the given data, according to what I found here: http://landshape.org/enm/options-for-acf-in-r/ this test data does not look IID but rather shows some trends so how can I