similar to: readline() for passwords?

Hello r-help, I have a couple of time-series of different length and I would like to produce a simple overview plot showing the autocorrelation functions of the series. The time-series are stored in a dataframe like this: > test.data item year value 1 xxx 1961 -1.09 2 xxx 1962 0.21 3 xxx 1963 -0.81 [trimmed] 8

I have a similar question, I know about --vsize, but I use R under Emacs using ESS. I know there is an easy way to call R from ESS with command line options but I don't remember how. I can't find help on this in ESS documentation or in R documentation. Could someone please remind me how this is done. ------------------------------------ | Robert Denham | |

I have a probably very naive question about the R anova/aov functions: I've found in several text books with descriptions of anova procedures that, in nested anova (specifying the model "X~A/B", B being a factor specifying treatments, and A groups of samples within each treatment), the mean square for "among treatments" is divided by the mean square "within treatment

Excuse me, if the following is FAQ or nonsense, I'm new to R (and the list)! After trying to import a textfile of 184897 Bytes, R (v0.63.0 on Linux 2.0.35/DLD 5.4) gives the following error message: > read.table ("db.out") Error: heap memory (1953 Kb) exhausted [needed 150 Kb more] > Is there a possibility to increase

Hello R experts, I haven't found anything like the S function 'varcomp' as described in W.N. Venables & B.D. Ripley's 'Modern Applied Statistics ...' for R; does something comparable exist for R, or is planned for future releases? More generally, are there libraries with post-anova test procedures, like Student-Newman-Keuls? Or do those of you who frequently use

Hello R-Experts, 2 questions: does anybody have example functions for determining the power of, say, a t-test or a single factor anova with fixed or random factors? and: is there an implementation of Cochran's test for heterogeneity of variances (i.e., is there a frequency distribution of Cochran's C)? Many thanks for your attention ... Ulf (please CC: me, I'm not on the

Testing for an NFS effect on the failure of 'make check': Try first on /usr/local/ 9:42 cd /usr/local/src/ 9:42 sudo mkdir R 9:43 sudo chown mdalphin:mdalphin R 9:43 cd R 9:43 gunzip -c /opt/apps/x86_64/R/Archive/R-3.2.5.tar.gz | tar xf - 9:43 cd R-3.2.5/ 9:44 ./configure --prefix=/opt/apps/x86_64/R/R-3.2.5 LIBnn=lib 9:44 make 9:57 make check

Hello out there, my first try to install a package (e.g. ctest from CRAN) didn't succeed; looking at the error messages I think it must be a configuration problem of my machine, but as I'm not very experienced I would be glad if someone could give me a hint ... R's version is 0.63.0, my i386-Linux is kernel 2.0.35. I hadn't had problems to compile R, and R itself seems to work.

Hi, Has anyone seen this problem before, and does anyone have a solution? When I query a database using DBI and ROracle to retrieve a date in a format other than the system default, I get a core dump. System: Redhat Linux 7.3 uname: Linux 2.4.20-20.7smp #1 SMP Mon Aug 18 14:46:14 EDT 2003 i686 Oracle version 8i R --version: R 1.7.1 (2003-06-16). DBI_0.1-6, ROracle_0.5-0 Start up R, load

Hello out there, in their "R Complements" to Modern Applied Statistics W. Venables and B. Ripley say that there is a lack of time series related functions in R compared to S plus. Looking at CRAN I didn't find much, too. As I have to learn something about +-basic ts analysis, e.g. spectral analysis, I would like to know whether somebody has developed a "unpublished" time

<<insert bug report here>> I had a "abnormal" exit of R plotting a fitted linear model. here's the last few lines of the R session: ------------------------------------------------------------------- > plot(blstrhz.lm) Hit <Return> to see next plot: Hit <Return> to see next plot: Hit <Return> to see next plot: X Error of failed request: BadValue

I'm trying to find a clever way to re-map data from a database query into a data.frame. Querying a database often returns a table (data.frame) like this: GeneID MethodID Value 6 1 123 6 2 456 6 3 987 7 1 234 7 3 432 8 2 190 8 3 34 8 1 864 Note that GeneID=7 doesn't have a value for MethodID=2. Note that GeneID=8 doesn't have the

Per Timo's direction, I decided to give the MasterUser a try in connecting my proxy to my destination server. This might allow for the use of 'secure password' for my clients that like to check that box by default. A couple of problems I'm running into running RC15: #1: My Proxy's SQL password_query line: password_query = SELECT a.clearpasswd AS password, v.storeIP AS host,

Dear list, What on earth is spec.pgram() normalized too? If you would like to skip my proof as to why it's not normed too the mean squared or sum squared amplitude of the discrete function a[], feel free too skip the rest of the message. If it is, but you know why it's not exact in spec.pgram() when it should be, skip the rest of this message. The issue I refer herein refers only too a

On Fri, Aug 26, 2016 at 06:44:05PM +0200, Ralph Böhme wrote: > > Cheerio! > -slow Still reviewing this - but a few things that will need changing: When adding the validate_nt_acl_blob() function in [PATCH 06/12] vfs_acl_common: move the ACL blob validation to a helper function this makes some of the existing function names in debug statements incorrect. Eg. validate_nt_acl_blob()

On Sat, Aug 27, 2016 at 12:46:12PM +0200, Ralph Böhme via samba wrote: > > ...and this one even has bug urls in all commit messages. Sorry for > forgetting this in the previous version. Juuuusttt *one* leetle change, sorry :-). I was following the changes to the talloc heirarchy in the code and realized that adding the following change made it much clearer (at least to me). diff --git

Hi, I have some very noisy, relatively sparse data; a biological response of roughly ~8 subjects at ~8 times points). I've been following the data trend using a lowess line, over-plotted with several values of bandwidth, 'f <- seq(0.3, 0.9, by=0.1)'. At this point, we have no models for these data. I wonder if there is any way under R to assign some sort of confidence interval to

Good Afternoon, I have the following code, but it seems that something must be doing wrong, because it is giving the results I want. The idea is to create segments while the value of Commutation is less than 1000. for example, from the small set of data below text=" val_user pos v v_star v_end commutation v_source v_destine 1 1 96-96 1173438391 1173438391 0

Hello, Maybe something like the following. splitDF <- function(data, col, s){ n <- nrow(data) inx <- which(data[[col]] %in% s) lapply(seq_along(inx), function(i){ k <- if(inx[i] < n) (inx[i] + 1):(inx[i + 1]) data[k, ] }) } splitDF(DF, "name", split_str) Hope this helps, Rui Barradas On 5/19/2018 12:07 PM, Christofer Bogaso

Dear list, I had some confusion regarding what function too use in order too relate results from spec.pgram() too a chi-square distribution. The documentation indicates that the PSD estimate can be approximated by a chi-square distribution with 2 degrees of freedom, but I am having trouble figuring out how to do it in R, and figuring out what specifically that statement in the documentation