similar to: Experimental Design

Hi all! I have 4 treatments on 5 animals Treat1 Treat2 Treat3 Treat4 Animal1 36 37 35 39 Animal2 33 34 36 37 Animal3 37 35 33 38 Animal4 34 36 34 35 Animal5 35 36 33 36 I use an Anova and i try to verify calcul So i retrieve: DF SS

Hi, I have been struggling with this problem for some time now. Internet, books haven't been able to help me. ## I have factorial design with counts (fruits) as response variable. > str(stubb) 'data.frame': 334 obs. of 5 variables: $ id : int 6 23 24 25 26 27 28 29 31 34 ... $ infl.treat : Factor w/ 2 levels "0","1": 2 2 2 2 1 1 1 2 1 1 ... $ def.treat :

Hi all, Two questions: 1. Is there a way to evaluate models from lmer() with a poisson distribution? I get the following error message: library(lme4) lmer(tot.fruit~infl.treat+def.treat+(1|initial.size),family=poisson)->model plot(fitted(model),resid(model)) Error: 'resid' is not implemented yet Are there any other options? 2. Why doesn't the function estimable() in gmodels

Dear R Users, Am using lm() with contrasts as below. If I skip the contrasts() statement, I get the coefficient names to be > names(results$coef) [1] "(Intercept)" "VarAcat" "VarArat" "VarB" which are much more meaningful than ones based on integers. Can anyone tell me how to get R to keep the coefficient names based on the factor levels

Can someone show me some code to do normalization by the median of some control genes for the example below? Many Many Thanks in advance This strategy selects a subset of genes (called ?control genes?) and makes the median of their data distribution similar across arrays. ??? ??? id1??? id2??? id3 control1??? 0.8??? 0.7??? 0.6 control2??? 0.6??? 0.2??? 0.4 probe1??? ??? 0.3??? 0.2??? 0.5

Here is my model with interaction terms and control variables (I changed variables names for easy read): reg1 <- lm(y ~ x1*x2*x3 +control1 + control2 + control3) x1 ranges from 0 to 6; x2 from 0 to 5; and x3 from 0 to 4. All three are discrete ordinal variables; but I will treat them as continuous variables. (a) How can I see the predicted values of y for each of these scenarios (210

Hi Michael- Since you bring up libquantum performance can you let me know what the IR will look like for this small code snippet (libquantum-like) with –enable-cond-stores-vec ? I ask because I don’t see vectorization kicking in unless -force-vector-width=<> is specified. Let me know if I am missing something. -Thx struct nodeTy { unsigned int c1; unsigned int c2; unsigned

I have data set up like the following: control1 <- sample(1:75, 3947398, replace=TRUE) control2 <- sample(1:75, 28793, replace=TRUE) control3 <- sample(1:100, 392733, replace=TRUE) control4 <- sample(1:75, 858383, replace=TRUE) patient1 <- sample(1:100, 28048, replace=TRUE) patient2 <- sample(1:50, 80400, replace=TRUE) patient3 <- sample(1:100, 48239, replace=TRUE) control

Dear list, Hello to everybody, I´m interested in finding a package for statistical analysis of binary data, I have a matrix with the following structure: Case1 Case2 Case 3 ....... CaseX Control1 Control2 Control3 ....... ControlY Pep1 1 0 1 1 0 0 0 1 Pep2 1 1 1 1 1 0 0 1 Pep3 0 1 1 1 1 0 0 1 ... Pepz 1 1 1 1 1 0 0 1 I would like to know some R package to calculte similarity matrix or

Hi Dibyendu, Are you using a recent compiler? What architecture are you targeting? The target will determine whether the vectorizer thinks vectorization is profitable without having to manually force the vector width. For example, top-of-trunk vectorizes your snippet with "clang -O2 -mllvm -enable-cond-stores-vec" and "--target=aarch64-unknown-linux-gnu". However, with

I haven't verified what Matt described is what actually happens, but assuming it is - that is a known issue in the x86 cost model. Vectorizing interleaved memory accesses on x86 was, until recently, disabled by default. It's been enabled since r284779, but the cost model is very conservative, and basically assumes we're going to scalarize interleaved ops. I believe Farhana is working

Hi Matt- Yeah I used a pretty recent llvm (post 3.9) on an x86-64 ( both AMD and Intel ). -dibyendu From: Matthew Simpson [mailto:mssimpso at codeaurora.org] Sent: Wednesday, December 14, 2016 10:03 PM To: Das, Dibyendu <Dibyendu.Das at amd.com> Cc: Michael Kuperstein <mkuper at google.com>; llvm-dev at lists.llvm.org Subject: Re: [llvm-dev] Enabling scalarized conditional stores in

If there are no objections, I'll submit a patch for review that sets the default value of "-enable-cond-stores-vec" to "true". Thanks! -- Matt On Wed, Dec 14, 2016 at 12:55 PM, Michael Kuperstein via llvm-dev < llvm-dev at lists.llvm.org> wrote: > I haven't verified what Matt described is what actually happens, but > assuming it is - that is a known

Thanks Michael and Dibyendu for doing the experimentation and bringing this up to our attention. It might be the case what Matt described here. I will take a look at it. Farhana From: Michael Kuperstein [mailto:mkuper at google.com] Sent: Wednesday, December 14, 2016 9:56 AM To: Das, Dibyendu <Dibyendu.Das at amd.com>; Aleen, Farhana A <farhana.a.aleen at intel.com> Cc: Matthew

Dear all, Using the data set and code below, I am interested in modelling how egg temperature (egg.temp) is related to energy expenditure (kjday) and clutch size (treat) in incubating birds using the lme-function. I wish to generate the F-distribution for my model, and have tried to do so using the anova()-function. However, in the resulting anova-table, the parameter kjday has gone from being

Hi Michael, Thanks for testing this on your benchmarks and target. I think the results will help guide the direction we go. I tested the feature with spec2k/2k6 on AArch64/Kryo and saw minor performance swings, aside from a large (30%) improvement in spec2k6/libquantum. The primary loop in that benchmark has a conditional store, so I expected it to benefit. Regarding the cost model, I think the

Package: src:xen Version: 4.8.1~pre.2017.01.23-1 Severity: wishlist Dear Maintainer, In Xen 4.8 it is possible to enable OVMF without the need for any OVMF code or binary to be on the system. Currently, OVMF is not enabled, probably because it used to require OVMF at compile time which would make for a hard dependency on non-free code. Since this is no longer the case, you could make it a

CentOS 6.2, Samba 4.0.0beta3, Bind 9.9.1-P1. I have a workking Bind9 installation which includes several different zone files. Foward and reverse lookups work fine. When I include include "/usr/local/samba4/private/named.conf"; in the named.conf, named will no longer start: Jul 9 15:01:47 s6a named[9857]: samba_dlz: started for DN DC=test,DC=cornell,DC=edu Jul 9 15:01:47 s6a

This series is mainly for testing live migration between 2 vdpa_sim_blk devices. The first patch is preparation and moves the buffer allocation into devices, the second patch adds the `shared_buffer_mutex` parameter to vdpa_sim_blk to use the same ramdisk for all devices. Tested with QEMU v8.0.0-rc2 in this way: modprobe vhost_vdpa modprobe vdpa_sim_blk shared_backend=true vdpa dev add mgmtdev

Hi All, I'm trying to use the geoRglm package to run a poisson spatial glm on a dataset with several covariates. When I run without covariates I have no problems. control1.data.geo <- mcmc.control(S.scale=0.2, thin = 1) model1.data.geo <- list(cov.pars = c(1,1), beta=c(1), family="poisson") test1.model1 <- glsm.mcmc(data.geo, model=model1.data.geo,