search for: herrdittmann

Dear useRs, With the rise of netbooks and 'lifestyle laptops" I am tempted to get one of these to mainly run R on it. Processor power and hard disk space seem to be ok. What I wonder is the handling and feel with respect to R. Has anyone here installed or is running R on one of these, and if so, what is your experience? Would it be more of a nice looking gadget than a feasable platform

Dear R-users, I am struggling to directly read an "op.gz" file into R. NOAA kindly provides daily weather data on their FTP server for download. > sessionInfo() R version 2.15.1 (2012-06-22) Platform: x86_64-pc-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United Kingdom.1252  LC_CTYPE=English_United Kingdom.1252    LC_MONETARY=English_United Kingdom.1252 [4]

Dear useRs, how can I construct a box&whisker plot based on the vector "fivenum"? The challenge I face is as follow: I have a table such as x | fivenum --------------- ... | (.....) ... | (.....) and so forth.... For each observation x I have generated a vector containing the fivenum estimates. The first challenge is to group my fivenum vectors into groups based on a

Hi useRs, I am trying to calculate the Sharpe ratio with "sharpe" of the library "tseries". The documentation requires the univariate time series to be a portfolio's cumulated returns. In this case, the example given data(EuStockMarkets) dax <- log(EuStockMarkets[,"FTSE"]) is however not the cumulated returns but rather the daily returns of the FTSE

Hi useRs, I have been running a regression of the following kind: > summary(lm(dx[2:2747] ~ 0 + (dx[1:2746]>15))) Call: lm(formula = dx[2:2747] ~ 0 + (dx[1:2746] > 15)) Residuals: Min 1Q Median 3Q Max -46.35871 -3.15871 0.04129 3.04129 30.04129 Coefficients: Estimate Std. Error t value Pr(>|t|) dx[1:2746] > 15FALSE

Hi useRs, Been estimating a VAR with two variables, using VAR() of the package "vars". Perhaps I am missing something, but how can I include the present time t variables, i.e. for the set of equations to be: x(t) = a1*y(t) + a2*y(t-1) + a3*x(t-1) + ... Y(t) = a1*x(t) + a2*x(t-1) + a3*y(t-1) + ... The types available in function VAR() allow for seasonal dummies, time trends and

Hi R-Group, I am stuck with the following problem: I am constructing a portfolio of 2 variables x and y x <- rnorm(100, mean=100, sd=4) y <- rnorm(100, mean=120, sd=10) which I am combining as follows to a portfolio for sampling purposes: portfolio <- c(rep(x, 8), rep(y, 2)) In this case I have assigned the weights of 8 and 2 to calculate the bootstrapped mean: mean.boot <-

Hello, How can an interative unit root test be implemented in R? More specifically, given a time series, I wish to perform the Dickey Fuller Test on a daily basis for say the last 100 observations. It would be interative in the sense that this test would be repeated each day for the last 100 observations. Given the daily Dickey Fuller estimates of delta for the autoregressive process d(Y(t))

Hi useRs, can a variance test for 2 non-normal samples be tested in R? Also, thus far I have not been able to find the Friedman two way analysis of variance. For normal r.v., the var.test is available, but are there any tests available for non-normal samples? Thanks! Bernd

Dear useRs, I am stuck with a piece of code and hope you could give me some pointers. My aim is to calculate the lm-regression coefficients of individual stocks against an index. I am interested in both the coefficient and the pval. While I could do this manually for a select hand full, I hope to scale this up say for 30+ stocks (DAX-30, FTSE-100 etc.) to eventually have a matrix of coefficients