similar to: [Bug 440] New: Protocol 1 server key generated at start up even when P1 not used

http://bugzilla.mindrot.org/show_bug.cgi?id=440 djm at mindrot.org changed: What |Removed |Added ---------------------------------------------------------------------------- Status|NEW |RESOLVED Resolution| |FIXED ------- Additional Comments From djm at mindrot.org 2003-05-15 21:16

http://bugzilla.mindrot.org/show_bug.cgi?id=440 ------- Additional Comments From markus at openbsd.org 2002-11-21 20:21 ------- when does this happen? i don't see this with version 3.5 (or 2.5.1) ------- You are receiving this mail because: ------- You are the assignee for the bug, or are watching the assignee.

http://bugzilla.mindrot.org/show_bug.cgi?id=440 ------- Additional Comments From dtucker at zip.com.au 2004-02-10 18:07 ------- Took a quick look at this. I can confirm that when running in inetd ("-i -o Protocol=1,2") the SSHv1 ephemeral keys are still generated for v2 connects, and that with the patch it's not. The patch, however, seems to break SSHv1 connections in inetd

https://bugzilla.mindrot.org/show_bug.cgi?id=440 Darren Tucker <dtucker at zip.com.au> changed: What |Removed |Added ---------------------------------------------------------------------------- Attachment #1429| |ok? Flag| | --- Comment #7 from Darren Tucker <dtucker at

We have AIX 4.3.3 ML09 and AIX 5.1 ML01 I have narrowed the problem down, it is nothing to do with uni/multiprocessor machines. Both rsync 2.3.1 compiled by Bull in an installp and a gcc compiled version of 2.4.5 ( by me ) both have exactly the same problem with SSH 3.1.p1 and both DONT have the problem with SSH 2.9.9p1 - so I assume this is something highly specific to SSH 3.1.1.p1 Hope this

All- I am interested in estimating a parameter that is the starting value for an ODE model. That is, in the typical combined fitting procedure using nls and lsoda (alternatively rk4), I first defined the ODE model: minmod <- function(t, y, parms) { G <- y[1] X <- y[2] with(as.list(parms),{ I_t <- approx(time, I.input, t)$y dG <- -1*(p1 + X)*G +p1*G_b dX <-

Hello - and sorry for a possibly stupid question, I'm just starting to learn rgenoud. I am defining a function with 5 parameters (p1, p2, p3, p4a, and p4b) and then want to optimize it using genoud. But I am doing something wrong. Before genoud is even able to run it says: "Error in p2 + 1.2 : 'p2' is missing". I assume I did not specify it right. My code is below. The task

Hello all, I am trying to produce the closed-form Ait-Sahalia approximation to the log-likelihood function of a diffusion process but the function arguments I am passing to the function result in NaN being returned. I've checked the 'Transform','S' and 'M' functions and the problem doesn't seem to be with these. Does anyone have any ideas why this isn't working?

I have 3 vectors: p1, p2, and p3. I would like each vector to be any possible value between 0 and 1 and p1 + p2 + p3 = 1. I want to graph these and I've thought about using scatterplot3d(). Here's what I have so far. library(scatterplot3d) p1 <- c(1,0,0,.5,.5,0,.5,.25,.25,.34,.33,.33,.8,.1,.1,.9,.05,.05) p2 <- c(0,1,0,.5,0,.5,.25,.5,.25,.33,.34,.33,.1,.8,.1,.05,.9,.05) p3 <-

Dear LLVMdev, I've noticed an unusual behavior of the LLVM x86 code generator (with default options) that results in nearly a 4x slow-down in floating-point throughput for my microbenchmark. I've written a compute-intensive microbenchmark to approach theoretical peak throughput of the target processor by issuing a large number of independent floating-point multiplies. The distance

Hi, I am wondering if anyone can propose a simple/best way to do the following: Let's say I have a data frame dat <- cbind(expand.grid(mode=c('right','left'),time=0:3,id=c('p1','p2','p3')),y=c(3,5,rep(4,6),6,2,rep(3,6),4,4,rep(2,6))) dat mode time id y 1 right 0 p1 3 2 left 0 p1 5 3 right 1 p1 4 4 left 1 p1 4 5 right 2

Installed using pkd_add or ports BIND-9.6.0-P1 working fine. 1.But seems can't run under chroot well: ---------------------------------------------------------- Jan 27 13:54:08 ns named[36447]: starting BIND 9.6.0-P1 -c named.conf -t /var/named -u bind Jan 27 13:54:08 ns named[36447]: built with '--localstatedir=/var' '--disable-linux-caps'

Among others, datam contains the columns: logconc, tm, dose, subj, bilirubin. None of these are factor variables. The following compartment models work (the first still has not converged after 100 interations): res1 <- nlme(logconc~p2+p3+log(dose/(exp(p1)-exp(p2))* (exp(-exp(p2)*tm)-exp(-exp(p1)*tm))),start=list(fixed=c(5,-2,-0.1)), fixed=list(p1+p2+p3~1),control=list(maxIter=100),

Send CentOS-announce mailing list submissions to centos-announce at centos.org To subscribe or unsubscribe via the World Wide Web, visit http://lists.centos.org/mailman/listinfo/centos-announce or, via email, send a message with subject or body 'help' to centos-announce-request at centos.org You can reach the person managing the list at centos-announce-owner at centos.org When

Dear all, I have two functions (f1, f2) and 4 unknown parameters (p1, p2, p3, p4). Both f1 and f2 are functions of p1, p2, and p3, denoted by f1(p1, p2, p3) and f2(p1,p2,p3) respectively. The goal is to maximize f1(p1, p2, p3) subject to two constraints: (1) c = k1*p4/(k1*p4+(1-k1)*f1(p1,p2,p3)), where c and k1 are some known constants (2) p4 = f2(p1, p2, p3) In addition, each parameter

Dear R user I follow the steps defined in Modern applied statistics page(453) to use optim. However, when I run the following code the parameters seems way off and the third parameter(p3) stayed as the initial value. below is the code: ## data da=c(418,401,416,360,411,425,537,379,484,388,486,380,394,363,405,383,392,363,398,526) ### initial values pars=c(392.25, 507.25, 0.80)

Dear R-experts, I have got a dataframe: data ID disease V1 V2 1 p1 1 2 p1 3 3 p3 3 4 p3 5 5 p5 1 From which I extract a usefull table: affect affect 1 3 5 p1 1 1 0 p3 0 1 1 p5 1 0 0 I want to merge this with anotherdataframe: age p1 23 p2 24 p3 23 p4 11 p5 45 If have tried as.data.frame(affect) and other solutions to get the following comment going:

Hello, In doing a series of non-linear estimations of a function which is a sum of a varying number of sinusoids, I would like to "autogenerate" the arguments needed by nls() depending on that number. For example, when there are two sinusoids: > nls( y ~ mu + A1 * cos(2*pi*f1*x - P1) + A2 * cos(2*pi*f2*x - P2), data = some.xy.data, start = list( mu=some.value0,

Dear list, Following up on an earlier post, I would like to reorder a dataset and compute pairwise correlations. But I'm having some real problems getting this done. My data looks something like: Participant Stimulus Measurement p1 s`1 5 p1 s`2 6.1 p1 s`3 7 p2 s`1 4.8 p2

Dear R users, I have to import some csv files in which column headers contain the character "~". Following the following import call, the character seems to be replaced by dots in the column names of my data frame. Plus, I cannot query names(mydata) to find the column index which header should contain "~" or "." > mydata <-