search for: iide

Tasty Planet loads, and then complains that a module is missing - WINMM.DLL I checked - wine DOES have this dll in it's system32 folder. Wine produces this log: Code: wine: Unhandled page fault on write access to 0x00650180 at address 0x7ee58a73 (thread 0021), starting debugger... Unhandled exception: page fault on write access to 0x00650180 in 32-bit code (0x7ee58a73). Register dump:

Hi R, I want to conduct iid tests. So, I went to download 'iid.test' package. And the dependent package is 'ncdf', which is not available. So, how do I conduct the IID tests? Can I do these iid tests in Base R? Thanks in advance, Shubha This e-mail may contain confidential and/or privileged i...{{dropped:12}}

It seems that Tablegen is generating intrinsic ID's off by in DAGISel.inc In DAGISel.inc, I have the following pattern: int64_t CN1 = Tmp0->getZExtValue(); // Pattern: (intrinsic_w_chain:f32 103:iPTR, GPRF32:f32:$src0, GPRF32:f32:$src1, GPRF32:f32:$src2) // Emits: (MACRO_FMA_f32:f32 GPRF32:f32:$src0, GPRF32:f32:$src1, GPRF32:f32:$src2) // Pattern complexity = 8 cost

Are you using isTarget = 1 in your intrinsics file? On Apr 14, 2009, at 6:34 PM, Villmow, Micah wrote: > It seems that Tablegen is generating intrinsic ID’s off by in > DAGISel.inc > > In DAGISel.inc, I have the following pattern: > int64_t CN1 = Tmp0->getZExtValue(); > > // Pattern: (intrinsic_w_chain:f32 103:iPTR, GPRF32:f32:$src0, > GPRF32:f32:$src1,

I downloaded the iid.test, but I can't run it. I get the following message: Error: could not find function "iid.test" Where am I supposed to save this package in order that it works? Thanks, EZ [[alternative HTML version deleted]]

Hi, I am trying to parameterize the following mixed model (following Piepho and Ogutu 2002), to test for a trend over time, using multiple sites: y[ij]=mu+b[j]+a[i]+w[j]*(beta +t[i])+c[ij] where: y[ij]= a response variable at site i and year j mu = fixed intercept Beta=fixed slope w[j]=constant representing the jth year (covariate) b[j]=random effect of jth year, iid N(0,sigma2[b]) a[i]=random

Se ha borrado un adjunto en formato HTML... URL: <https://stat.ethz.ch/pipermail/r-help-es/attachments/20141023/57649d5c/attachment.html>

when i try to run any d3d app i get this error: fixme:ddraw:Main_DirectDraw_SetCooperativeLevel (0x403a2748)->(0000013c,00000008) fixme:ddraw:MESA_IDirect3DImpl_EnumDevices (0x403a0f9c)->(0x41c2f4,0x420516ac),stub! fixme:ddraw:Main_DirectDraw_SetCooperativeLevel (0x403a2a68)->(0000013c,00000011) fixme:ddraw:MESA_IDirect3D2Impl_CreateDevice

hello, i need to calculate ci's for each of 4 groups within a dataset, to be able to infere about differences in the variable "similarity". the problem is that data within groups is dependent, as assigned by the blocking-factor "site". my guess was to use a block bootstrap but samples within in these blocks / sites are not of same length. i was not able to find a method to

Dear R-Users, I can't understand the behaviour of quasibinomial in lmer. It doesn't appear to be calculating a scaling parameter, and looks to be reducing the standard errors of fixed effects estimates when overdispersion is present (and when it is not present also)! A simple demo of what I'm seeing is given below. Comments appreciated? Thanks, Russell Millar Dept of Stat U.

Dear all, I noticed the following behaviour of plot.lm: > fm1 <- lm(time~dist, data=hills, weights=c(0,0,rep(1,33))) > par(mfrow=c(2,2)) > plot(fm1) Warning messages: 1: longer object length is not a multiple of shorter object length in: res/(sd * (1 - hat)) 2: longer object length is not a multiple of shorter object length in: (res/(sd * (1 - hat)))^2 * hat which seems to be

Hi,everybody I have a dataframe like this FID IID STATUS 1 4621 live 1 4628 dead 2 4631 live 2 4632 live 2 4633 live 2 4634 live 6 4675 live 6 4679 dead 10 4716 dead 10 4719 live 10 4721 dead 11 4726 live 11 4728 nosperm 11 4730 nosperm 12 4732 live 17 4783 live 17 4783 live 17 4784 live

Dear All: I am trying to calculate four columns' means in a dataframe like this: FID MID IID EW_INCU EW_17.5 EMW EEratio 1 4621 TWF2H5 45.26 NA 15.61 NA 1 4621 TWF2H6 48.02 44.09 13.41 0.3041506 2 4630 TWF2H19 51.44 47.81 NA NA 2 4631 TWF2H21 NA 52.72 16.70

Hello, I am working from a linux 64 machine on a server with R-2.12 (I can't update to 2.13). I am iterating through many linear mixed models for longitudinal data and I occasionally receive the following convergence error: > BI.lme <- lme(cd4 ~ time + genBI + genBI:time + C1 + C2 + C11 + C12, random =~ 1 + time | IID, data = d) Error in lme.formula(cd4 ~ time + genBI + genBI:time +

It looks like my CentOS 4.2 box is attacking other people with some type of ftp attack. I got an email from somebody saying they were being attacked by my IP address. Further investigation /var/log/messages shows a whole bunch of sshd attacks on me, none of which appear successful. I'm running ethereal right now and I can see that my system is doing some kind of ftp attacks on others.

Hi Is there any way to fit a bivaraite longitudinal mixed model using R. I have a data set with col names resp1 (Y_ij1), resp2 (Y_ij2), timepts (t_ij), unit(i) j=1,2,..,m and i=1,2,..n. I want to fit the following two models Model 1 Y_ij1, Y_ij2 | U_i = u_i ~ N(alpha + u_i + beta1*t_ij, Sigma) U_i ~ iid N(0, sigu^2) Sigma = bivariate AR structure alpha and beta are vectors of order 2.

I need to calculate the probability that a sample quantile will exceed a threshold given the size of the iid sample and the parameters describing the distribution of each observation (normal, in my case). I can compute the probability with brute force simulation: simulate a size N sample, apply R's quantile() function on it, compare it to the threshold, replicate this MANY times, and count the

Hi, lme() users, Can some one tell me how to do this. I model Orthodont with the same G for random variables, but different R{i}'s for boys and girls, so that I can get sigma1_square_hat for boys and sigma2_square_hat for girls. The model is Y{i}=X{i}beta + Z{i}b + e{i} b ~ iid N(0,G) and e{i} ~ iid N(0,R{i}) i=1,2 orth.lme <- lme(distance ~ Sex * age, data=Orthodont, random=~age|Subject,

Dear R-experts Execuse me for an easy question, but I need help, sorry for that. >From days I have been working with a large dataset, where operations are needed within a component of dataset. Here is my question: I have big dataset where x1:.....x1000 or so. What I need to do is to work on 4 consequite variables to calculate a statistics and output. So far so good. There are more vector

Someone just sent me a data set that causes the lmekin function, part of the kinship package, to fail. In chasing it down I get an error I have never seen before. fit <- lmekin(icam1 ~ factor(center) + age + factor(sex), random= ~1|iid, data=chaidata, varlist=kmat) Error in Y - fitted : non-numeric argument to binary operator Add the recover option, and the offending lines are