similar to: how to use list index to get vector

Hello, after splitting a data-frame I want to access the results. Maybe the problem is, that the factor/index is a string... ...or do I miss knowing details of the index-uasge? Please look and help: ======================================= > weblog <- read_weblog("web.log") > > > str(weblog) 'data.frame': 2247 obs. of 18 variables: $ host : Factor w/ 77

I would like to take the values of observations and map them to a new index. I am not sure how to accomplish this. The result would look like so: x[1,2,3,4,5,6,7,8,9,10] becomes y[2,4,6,8,10,12,14,16,18,20] The "newindex" would not necessarily be this sequence, but a sequence I have stored in a vector, so it could be all kinds of values. here is what happens: > x <- rnorm(10)

Hello! # I have a data frame: mydf<-data.frame(c1=rep(NA,5),c2=rep(NA,5),c3=rep(NA,5)) # I have an index whose length is always the same as nrow(mydf): myindex<-c(1,2,3,2,1) # I need c1 to have 1s in rows 1 and 5 (based on the information in myindex) # I need c2 to have 1s in rows 2 and 4 (also based on myindex) # I need c3 to have 1 in row 3 # In other words, I am trying to achieve this

Hi, I am searching for the equivalent of the function Index from SAS. In SAS: index("abcd", "bcd") will return 2 because bcd is located in the 2nd cell of the abcd string. The equivalent in R should do this: > myIndex <- foo("abcd", "bcd") #return 2. What is the function that I am looking for? I want to use the return value in substr, like I do

When I used svmlight, I got below error: my command is: foo <- svmlight(y~., data= myData) the results: Error in file(con, "r") : unable to open connection In addition: Warning messages: 1: svm_learn not found 2: cannot open file '_model_1.txt' > myData[1:2,] y X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 1 1 63 1 0 0 145 233 1 1 0 150 0 2.3 1

Dear R users, glm.fit() gave me the same AIC's regardless of TRUE or FALSE intercept option. > myX <- as.matrix(1:10) > myY <- 3+5*myX > foo <- glm.fit(x=myX, y=myY, family = gaussian(link = "identity"), intercept=TRUE) > foo$aic [1] 38.94657 > foo <- glm.fit(x=myX, y=myY, family = gaussian(link = "identity"), intercept=FALSE) > foo$aic [1]

Is there a fast way to determine how many documents a term occurs in, besides iterating through every document with TermDocEnum? -- Best regards, Stian Gryt?yr

Dear R users, I'm starting to use 'apply' functions rather than for loops in R, and sometimes the output is a bit different than what I want. In this case, the command was tapply(myvector,myindex,cumsum) And the output was something like this: $`SNRL1 Core 120` [1] 2.8546 4.0778 5.2983 6.3863 7.5141 8.5498 9.5839 10.6933 $`SNRL1 Core 230` [1] 7.6810 8.7648 9.8382

Hi, I wonder about the performance of a Linux box used as router (I guest I''m not the first :). Althought I know it mainly depends on the hardware, I''m trying to find some references on the topic or comparations with other routing solutions (FreeBSD box used as router, Cisco, etc). For example, http://facweb.cti.depaul.edu/jyu/Publications/Yu-Linux-TSM2004.pdf (althought is

If I try the following: class foo { define bar ($text) { file {"/tmp/foo.txt": content => $text, } } bar { "hello": text => ''Hello World'', } } class foo2 inherits foo { Foo::bar["default"] { text => ''Hello World Again'', } } I get: "Syntax error at '':''; expected

Hi I have within a quite big function foo1, an internal function foo2. Now, in order to have a cleaner code, I wish to have the internal foo2 as "external". This foo2 was using arguments within the foo1 environment that were not declared as inputs of foo2, which works as long as foo2 is within foo1, but not anymore if foo2 is external, as is the case now. Now, I could add all those

Hello! Say I have a function foo1, which has argument ... to pass various arguments to foo2 i.e. foo1 <- function(x, ...) { foo2(x, ...) } Say that foo2 accepts argument arg1 and I would like to do the following: - if foo1 is called as foo1(x) then I would like to assign some value to arg1 inside foo1 before calling foo2 arg1 <- "some value" foo2(x, arg1=arg1) - if foo1 is

please see the code below. foo2 fails to dispatch correctly, but foo does fine. i have tried 'cacheMetaData(1)' and a number of different variants of 'cacheGenericsMetaData', on the possibility there is a caching issue. but i still can't sort it out. also one general question: does it really matter what's in the body of the function definition in a

Thank you very much for your useful suggestions. These are exactly what I was looking for. foo <- list(foo1, foo2, foo3) lapply(foo, function(x) matrix(unlist(x), nrow = length(x), byrow = TRUE)) or lapply(foo, function(x) do.call('rbind', x)) Best, Muhammad Subianto On 4/11/06, Muhammad Subianto <msubianto at gmail.com> wrote: > Dear all, > I have a result my experiment

Dear all, I have a result my experiment like this below (here my toy example): foo1 <- list() foo1[[1]] <- c(10, 20, 30) foo1[[2]] <- c(11, 21, 31) foo2 <- list() foo2[[1]] <- c(100, 200, 300) foo2[[2]] <- c(110, 210, 310) foo3 <- list() foo3[[1]] <- c(1000, 2000, 3000) foo3[[2]] <- c(1100, 2100, 3100) list(foo1,foo2,foo3) The result: > list(foo1,foo2,foo3) [[1]]

Hi the list, I define a method that want to change an object without assignation (foo(x) and not x<-foo(x)) using deparse and assign. But when the argument of the method does not match *exactly* with the definition of the generic function, assign does not work... Anything wrong? Christophe #------ Does not work ------#

an obvious fix to PIC IO intercept. In PIC IO, address from send_pio_req is physical address already. Signed-off-by: Xiaohui Xin <xiaohui.xin@intel.com> Signed-off-by: Xiaowei Yang <xiaowei.yang@intel.com> Signed-off-by: Xin Li <xin.b.li@intel.com> _______________________________________________ Xen-devel mailing list Xen-devel@lists.xensource.com

Hi all, For some reason, I would like to use functions bellow (see example code bellow), but instead I get the following error message: *Error in foo2(...) : unused argument(s) (arg3 = 3)* #--------------------- # example code #--------------------- foo1 <- function(arg1,...) { print(arg1) foo2(...) foo3(...) } foo2 <- function(arg2) { print(arg2) } foo3 <- function(arg3) {

Dear R-devel, I'm trying to validate the results from a C function, against a (trial and tested) older R function. For reasons unknown to me, the C function seems to give different result sometimes at each trial, even with the very same data. These are the relevant outputs from R: > library(QCA) Loading required package: lpSolve > benchmark <- function(x, y) { + index <- 0

Hi to all Authors@R: c(person("fooa","foob", role = c("aut","cre"), email = "fooa.foob@fooc.de"), person("foo1","foo2", role = c("ctb"), email = "foo1.foo2@foo3.de")) Author: fooa foob, with contributions from foo1 foo2 using r CMD check --as-cran .. (R 3.1