similar to: substitute, eval and hastables

Sorry for the stupid question, but is there the factorial function in R? I tried to find it using help.search('factorial') but got nothing appropriate. Many thanks, -Serge

Hi there; I have the following problem --- Xemacs cannot correctly parse a path to file when I load it. I have the following error, reported by Xemacs: from ess-parse-errors: Error in file(file, "r") : cannot open file `u:US-mortalityjuttalexible.r While the correct file path should be: u:\US-mortality\jutta\flexible.r Any ideas? Many thanks for your help. -Serge

Hi, I'm working on a plugin for qpsmtpd (a perl smtp frontend) that delivers mail via dovecot's LDA. I can only get mail delivered by writing the email to file, then calling 'deliver -d someone -f someone-else < /path/to/temp/email' All good, expected behavior. A perl snippet: local $/=undef; open FH, "< ./demo.mail"; my $stringified = <FH>; # this is

This is something between a question and a bug report. {sometimes one should first ask on R-help before sending to R-bugs....} I wanted to plot (.) a formula with "..." ## Works : e0 <- expression(T(x[1],...x[n])*", "*N[1] == 101) # works ok plot(1, main = e0) ## Now, need substitute, to replace with value of variableThis works nn <- 102 (e1 <-

Hi, Is there any particular reason why the Debian repositories (at http://download.gluster.org/pub/gluster/glusterfs/LATEST/Debian/ ) only have packages for amd64? I don't mean to pressure for more convenience; I'm just wondering if there's any reason to avoid using it on i386.

Hello, I use nnet to do prediction for a continuous variable. after that, I calculate correlation coefficient between predicted value and real observation. I run my code(see following) several time, but I get different correlation coefficient each time. Anyone know why? In addition, How to calculate prediction accuracy for prediction of continuous variable? Aimin thanks, > m.nn.omega

Hi! I'm running 1.1rc4 on a system and this happens occasionally: --8<-- mail.info; dovecot: auth(default): client in: AUTH 1 PLAIN service=imap lip=NN.NN.NN.NN rip=NNN.NN.NNN.NN lport=143 mail.info; dovecot: auth-worker(default): pam(XXXXXXXXXXXX,NNN.NN.NNN.NN): lookup service=imap kern.alert; kernel: grsec: From NN.NN.NN.NN: denied resource overstep by requesting

Hello, (Apologies for length, wanted to get all the relevant detail in that I know of). I've been having a lot of trouble with some code for an inventory analysis problem I was doing, and finally came to the conclusion that it appears that choose() is returning incorrect values. Specifically: ------------- Browse[1]> nn [1] 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3

Outbound calls on my Telus PRI aren't taking the Name portion of the callerID. I've looked at the logs, and it is being set (see below), but the PRI debug output doesn't show the name being sent anywhere. As a result, received calls always display from Unknown (or just the number). Is there some config that I've missed somewhere? I'm running NI-1 (Telus says NI-2 doesn't

Group It's unlikely I'm trying this the best way, but I'm trying to create a data structure from elements like nNode = 2 nn = vector("list",nNode) nn[[1]] = list(Node = "1", Connect.up = c(NULL), Connect.down = c(2,3)) nn[[2]] = list(Node = "2", Connect.up = c(1), Connect.down = c(4,5)) .... #( and eventually many more nodes) NodeList =

Is this a bug, or have I misunderstood the proper use of lm? Thanks, Whit code: x <- rnorm(50) y <- matrix(as.logical(round(runif(100),0)),ncol=2) NROW(x)==NROW(y) lm(x~y) > x <- rnorm(50) > y <- matrix(as.logical(round(runif(100),0)),ncol=2) > NROW(x)==NROW(y) [1] TRUE > lm(x~y) Error in "[[<-.data.frame"(`*tmp*`, nn, value = c(2, 1, 2, 1, 1, 1, 2, :

Dear R-list, I try to transform a mathematica script to R. #######relevant part of the Mathematica script (* p_sv *) dd = NN (DsD - DD^2); lownum = NN (L-DD)^2; upnum = NN (H-DD)^2; low = lownum/(2s^2); up = upnum/(2s^2); psv = NIntegrate[1/(s^NN) Exp[-dd/(2s^2)] (Gamma[1/2,0,up] + Gamma[1/2,0,low]),{s,sL,sH}, MinRecursion->3]; PSV = psv/Sqrt[2NN]; Print["------------- Results

Folks, Updating values in a table is simple in SAS or SQL, but I've wracked my brain looking for an elegant solution in R to no avail thus far. Certainly this is a common need that's been solved in dozens of different ways. Given an initial dataframe nn and a smaller dataframe of updates uu, I'd like to replace the values in nn <- expand.grid('a'=1:4, 'b'=1:3)

Sat, 06 Dec 2014 07:19:29 +1300 from Andrew Bartlett <abartlet at samba.org>: >On Fri, 2014-12-05 at 11:50 +0300, ?????? wrote: >> Hi All >> >> Having problem to join Samba as BDC in existing domain >> >> PDC - w2003 >> >> Partition[DC=MKS,DC=lan,DC=net] objects[10114] linked_values[0] >> Refusing to replicate

> t(t(NN)/lambda) [,1] [,2] [,3] [1,] 0.5 0.6666667 0.75 [2,] 2.0 1.6666667 1.50 > R matrices are column-based. MATLAB matrices are row-based. > On Feb 27, 2024, at 14:54, Evan Cooch <evan.cooch at gmail.com> wrote: > > So, trying to convert a very long, somewhat technical bit of lin alg > MATLAB code to R. Most of it working, but raninto a stumbling block

I decided to do a direct comparison of transpose and sweep. library(microbenchmark) NN <- matrix(c(1, 2, 3, 4, 5, 6), nrow = 2, byrow = TRUE) # Example matrix lambda <- c(2, 3, 4) # Example vector colNN <- t(NN) microbenchmark( sweep = sweep(NN, 2, lambda, "/"), transpose = t(t(NN)/lambda), colNN = colNN/lambda ) Unit: nanoseconds expr min lq

Dear Sir: When I try to save large and very complex recursive objects with some components containing models (such as the output from arima or lm ), the resulting file sizes increase by 4 meg per save. example directory: amex 8 meg argentina 12 meg australia 16 meg ... Moreover, I am unable to read these file objects back into R. I note that readBin and writeBin

I have a conceptual problem (sort of). Maybe there's a simple solution, maybe not. First, let me explain the test case that goes ok. Let x be a (fixed) n-dimensional vector. I simulate a lot of linear models, y = m x + c + error, then I do a lot of regressions. As expected, the estimated values of m (let's call them m.bar) are distributed according to a Student's t distribution.

Hi, I have the following problem. It has two parts. 1. I need to calculate the stationary probabilities of a Markov chain, eg if the transition matrix is P, I need x such that xP = x in other words, the left eigenvectors of P which have an eigenvalue of one. Currently I am using eigen(t(P)) and then pick out the vectors I need. However, this seems to be an overkill (I only need a single

Why anything but sweep? The fundamental data type in Matlab is a matrix... they don't have vectors, they have Nx1 matrices and 1xM matrices. Vectors don't have any concept of "row" vs. "column". Straight division is always elementwise with recycling as needed, and matrices are really vectors in row-major order: 1 2 3 4 5 6 is really 1 4 2 5 3 6 and when you do