similar to: constraints again

Hi, I'm having a problem using sample() within a function. Basically I get an error reading: Error in sample(v, 1, prob = h) : non-positive probability Can anyone advise me as to the possible origin of this error? Here is my code #Discretised Gillespie algorithm function (From SMfSB, D.J. Wilkinson) gillespied=function (N, T=100, dt=1, ...) { tt=0 n=T%/%dt x=N$M

Dear List, This is just a programming problem which i cannot seem to figure out. I am trying to get a set of power from a test (say, kolmogorov smirnov) out of a distribution (say, G-K distribution) as follows. I am trying to reduce to pain of writing the whole set of data points (p# below) using "for" loop. However, I seem to have some problem in it as the output "M" does not

All - I have a large data frame that looks like ID p1 p2 p3...p20 Lat1 Lat2 Lat3...Lat20 Long1 Long2 Long3...Long20 1 0 0 1 0 NA NA 29.xx NA NA NA -89.xx NA 2 1 0 0 1 27.xx NA NA 29.00 -88.00 NA NA -89.xx 3 0 0 0 0 NA

Hi, All, I'm trying to build a customized backend and I need to lower the formal arguments like this: There are several specific registers just for storing formal arguments. And also there are several general purpose registers for computation. If there is an instruction which uses parameters, I should first use a move instruction, which moves the value to general purpose register. For

Pipe's a strange syscall. Here is a fix for ia64. mh -- Martin Hicks Wild Open Source Inc. mort@wildopensource.com 613-266-2296 # This is a BitKeeper generated patch for the following project: # Project Name: The kernel C library # This patch format is intended for GNU patch command version 2.5 or higher. # This patch includes the following deltas: #

Hello all, I am running a simple path analysis with the function sem.mi (of semTools) after doing multiple imputation in my (missing) data. However, depending on the option to combine the chi-square, I get the following warning messages: Warning messages: 1: In estimateVCOV(lavaanModel, samplestats = lavaanSampleStats, ... : lavaan WARNING: could not compute standard errors! 2: In

Hi everyone, I'm observing what I believe is weird behaviour when attempting to do something very simple. I want a correlation matrix, but my matrix seems to contain correlation values that are not found when executed on pairs: > test2$P2 [1] 2 2 4 4 1 3 2 4 3 3 2 3 4 1 2 2 4 3 4 1 2 3 2 1 3 > test2$HP_tot [1] 10 10 10 10 10 10 10 10 136 136 136 136 136 136 136 136 136

Hi. The patch I send before was too large so that it was dropped from the maling list. I'm sending again with smaller size. This patch set is the xen paravirtualization of hand written assenbly code. And I expect that much clean up is necessary before merge. We really need the feed back before starting actual clean up as Eddie already said before. Eddie discussed how to clean up and suggested

Hi. The patch I send before was too large so that it was dropped from the maling list. I'm sending again with smaller size. This patch set is the xen paravirtualization of hand written assenbly code. And I expect that much clean up is necessary before merge. We really need the feed back before starting actual clean up as Eddie already said before. Eddie discussed how to clean up and suggested

I'm currently using Asterisk running version 1.2.5 and trying to use cdr_odbc to connect to a Microsoft SQL database. I have everything running, but the insert statement being sent to database doesn't appear to have the "start, answer, end" information in it. Below is the insert statement that MS Profiler shows being sent. As you can see those fields are missing. INSERT INTO

Hi, This is a quiet a specific question, but i really need help. I'm using the flowCore package coming from BioConductor. No i would like to do a transformation, a log tranformation. Although i think i put everything like it should, i get this error: Error in log(x, logbase) : Non-numeric argument to mathematical function which looks like a general calculating problem. the code i use now

The parts of klibc specific to the ia64 architecture. Signed-off-by: H. Peter Anvin <hpa at zytor.com> --- commit 951dc85bd690c6cc5a971815665da947160cbe51 tree 0843c8aa67a3c46a362d12c392c41c25d85ac9cd parent bd0599e5290ca1a16bb7a68f7c362d395c612eb3 author H. Peter Anvin <hpa at zytor.com> Sun, 25 Jun 2006 16:58:24 -0700 committer H. Peter Anvin <hpa at zytor.com> Sun, 25 Jun

class Array # break an array up into <size> chunks def chunk(size=1) return self if self.empty? raise ArgumentError if !size.kind_of? Integer y = self.length.divmod(size) rows = (y[1] > 0) ? y[0] + 1 : y[0] arr = Array.new(rows) (0...rows).each do |i| arr[i] = self.slice(size*i, size) end (arr.last.length...size).each { |i| arr.last[i] = nil }

Hi, In llvm/test/Transforms/InstCombine/cast.ll there is a test like this: target datalayout = "E-p:64:64:64-p1:32:32:32-p2:64:64:64-p3:64:64:64- a0:0:8-f32:32:32-f64:64:64-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:32:64- v64:64:64-v128:128:128-n8:16:32:64" [...] define <3 x i32> @test60(<4 x i32> %call4) { ; CHECK-LABEL: @test60( ; CHECK-NEXT: [[P10:%.*]] = shufflevector

Question for 'experts' in LP using R (using the lpSolve package, say) -- which does not apply to me for the sort of problem I describe below. I've run any number of LP's using lpSolve in R, but all of them to date have objective and constraint functions that both contain the same variables. This lets you set up a LHS and RHS matrix/vector that are symmetrical. But, for a

Apart from the fact that the statement "such that t1+t2+t3+t4=2970 (as it must)" is not correct, the LP can be implemented as follows: library(lpSolve) LHS <- rbind( c(0,0,0,0, 1, 0, 0,0), c(1,0,0,0,-1, 1, 0,0), c(0,1,0,0, 0,-1, 1,0), c(0,0,1,0, 0, 0,-1,1), cbind(-diag(4),diag(4)), c(0,0,0,0,0,1,0,0), c(0,0,0,0,0,0,1,0), c(0,0,0,0,0,0,0,1) ) RHS <-

I am trying to run an ANCOVA with defined error terms. Thus I have to use AOV and not lm. my response variable is proportion of mice paw prints on track plates. These plates were placed on plots that had vegetation and fruit manipulated to two levels each (present or absent), and were sampled monthly for 14 months (repeated measures). The fully crossed factor design was also blocked. My sample

Hi. I rewrote the patch according to the comments. I adopted generating in-place code because it looks the quickest way. The point Eddie wanted to discuss is how to generate code and its ABI. i.e. in-place generating v.s. direct jump v.s. indirect function call Indirect function call doesn't make sense because ivt.S is compiled multi times. And it is up to pv instances to choose in-place

Hi. I rewrote the patch according to the comments. I adopted generating in-place code because it looks the quickest way. The point Eddie wanted to discuss is how to generate code and its ABI. i.e. in-place generating v.s. direct jump v.s. indirect function call Indirect function call doesn't make sense because ivt.S is compiled multi times. And it is up to pv instances to choose in-place

I am using the gnls procedure in nlme package to fit a nonlinear model as: nl.fit<-gnls(Y ~ b0*exp(b1/X), data = data1, params=list( b0~p1+I(p1^2)+p2+I(p2^2)+p3+I(p3^2)+p5+p6 b1~p8+p2+I(p2^2)+p3+p9+p10+p11), start = c(25,0,0,0,0,0,0,0,0,-8.6,0,0,0,0,0,0,0), weights=varPower(form =~ X)