similar to: Need computing of Correlation Integral

Hello, I would like to use the BDS test from the tseries package, but there is something I don't understand in the results of the test. Let's say, I want the BDS values for an embedding dimension equal to 2 : > bds.test(c, m = 2, eps = seq(0.5 * sd(c), 2 * sd(c), length = 4),trace=FALSE); Here are the outputs: data: c Embedding dimension = 2 Epsilon for close points = 0.0097

Dear Sir, I’am a frensh student and i’am a new user of the R software. After using the command (x<-read.delim(“clipboard”) to read a spreadsheet of Excel, I want to run the bds test and calculate the Lyapunov exponent. I have charged the R software by the packages tseries and tseriesChaos. when i run bds.test(x,m=2) Unfortunately the R software displays “error in as.vector(x,mode= “double”) :

UseRs, I want to do a bds.test but the function return this : > bds.test(erro.exp,m=15); Error in as.vector(x, mode = "double") : (list) object cannot be coerced to double How can I fix this problem? Thanks savano [[alternative HTML version deleted]]

I make quite a lot of use of irregular time-series, and had already spent a bit of time writing an 'its' class when the 'irts' class was released via the package 'tseries'. I have experimented with the 'irts' class, and have some practical issues with its use. In some applications of irregular time-series (in my case these are financial and econometric) there are

I'm analizing the Argentina stock market (merv) I download the data from yahoo library(tseries) Argentina <- get.hist.quote(instrument="^MERV","1996-10-08","2003-11-03", quote="Close") merv <- na.remove(log(Argentina)) I made the Augmented Dickey-Fuller test to analyse if merv have unit root: adf.test(merv,k=13) Dickey-Fuller = -1.4645,

Hallo! I lese gro?e Zeitreihen in R ein z.B. mit: > disc<-read.table("F:/R/DATA/discount_rate_usa.txt") disc hat dann folgende Struktur: > disc[1:5] V1 V2 1 01/03/1955 1.5 2 01/04/1955 1.5 3 01/05/1955 1.5 4 01/06/1955 1.5 5 01/07/1955 1.5 ich will das disc als Zeitreihe erkannt wird und will z.B 01/03/1955 in ein Datum verwandeln, aber es wird als

Does R have a comparison operator similar to the Like function, for example: a<-"Is a Fish" b<-"Fish" if(b in a){c<-TRUE} Michael R Howard Micron Technology Inc. Boise ID. Fab C Engineering Software (FCES) Software Engineer

Hi all, I downloaded a R package (supclust, not from CRAN) in my directory, then type: markov:/home/pingzhao> R CMD INSTALL supclust_1.1.tar.gz -l ~/lib but met the following errors * Installing *source* package 'supclust' ... ** libs /usr/local/lib/R/bin/SHLIB: make: not found ERROR: compilation failed for package 'supclust' Does it mean the R has not properly installed?

Dear All I am trying to include sampling weights in multilavel regression analysis using packege lme4 using following codes print(fm1 &lt;- lmer(DC~sex+age+smoker+alcohol+fruits(1|setting), dataset,REML = FALSE), corr = FALSE) print(fm2 &lt;- lmer(DC~sex+age+smoker+alcohol+fruits(1|setting), dataset,REML = FALSE), corr = FALSE,weights=sweight) The problem is both the

Hi useRs, Many studies of the link between red meat and colorectal cancer use Cox proportional hazards with (among other things) a gender covariate. If it is true that men eat more red meat, drink more alcohol and smoke more than women, and if it is also true that alcohol and tobacco are known risk factors then why does it make sense to "adjust" for gender? I would think that in this

I tried to install the package "tseries" but could not do so. Any suggestions are welcome. I am using Ubuntu Linux and here is what I did: $ sudo R Then once in R, I did > install.packages("tseries", dep=TRUE) which gave a long list of errors. Going through them, I saw that the basic problem was that the package "grid" was not found by the packages (like

Dear all I have a character vector of dates something like: timevec<-c("15.5.2003 00:00", "15.5.2003 00:01", "15.5.2003 00:02", "15.5.2003 00:03","15.5.2003 00:04") and I would like to transform it to some more convenient date class. Is there a way how to do it directly without previous reformating to ISO like structure and adding a

Dear all, Is there a test in R for the randomness of a sequence of observations (e.g. to test the random number generator)? Specifically I am looking for autocorrelations which are not necessarily linear in nature, which the acf function does not seem to be flexible enough to detect as it tests for linear autocorrelation. Thanks in advance, Paul.

Fritz just put the first version of a new time series package to the contrib section at CRAN. The package is called "tseries.tgz" and provides a library for time series analysis. It contains acf Autocorrelation Function adf.test Augmented Dickey-Fuller Test amif Auto Mutual Information Function bds.test BDS Test

Fritz just put the first version of a new time series package to the contrib section at CRAN. The package is called "tseries.tgz" and provides a library for time series analysis. It contains acf Autocorrelation Function adf.test Augmented Dickey-Fuller Test amif Auto Mutual Information Function bds.test BDS Test

Hello R group, I'm using the tseries package to forecast variance and I would like to do the same with correlation. I can't find any way to do that with the function garch(). for example, I have a matrix of time series Date CACIndex SPXIndex DAXIndex NKYIndex 1 05/01/1998 3072.84 977.07 4384.81 14896.1 2 06/01/1998 3037.73 966.58 4352.63 14896.40 3

Hi, I have a factor and I would like to find the most frequent level. I think my current approach is a bit long winded and I was wondering if there was a more elegant way to do it: x <- factor(sample(1:0, 5,replace=TRUE)) levels(x)[ which( as.logical((table(x) == max(table(x)))) == TRUE ) ] (The length of x will always be an odd number, so I wont get a tie in max()) Thanks,

Hi All, I am trying to use llvm compiler to translate a non-trivial piece of code from C++ to C. I need this because I need to use part of the code as lib for another project that is strictly C. I am working under MSWin and I have choice to use either BCC or MSVC. After a good deal of tries I found out I had to somewhat massage llc -march=c output to make it *almost* compilable. I have one

I have a client with a handful of USB drives connected to a CentOS box. I am charged with binding the USB drives together into a single LVM for a cheap storage data pool (10 x 1 TB usb drives = 10 TB cheap storage in a single mount point). The next fun piece is how to incorporate that storage space into an existing Active Directory structure to apply AD acls for limited access. I'd rather

I have data in a file named hands.dat, which is given at the end of this question. (It's from a stats textbook example on anova). I'd like to do an aov on this, which I guess would be d <- read.table("~/hands.dat", header=TRUE) aov(Bacterial.Counts ~ Water + Soap + Antibacterial.Soap + Alcohol.Spray, data=d) but this fails. Do I need to break d$Method up into columns for