similar to: Contrasts for ordered factors

How can I get the result of, e.g., poly(1:3. degree=2) to give me the unnormalized integer coefficients usually used to explain orthogonal polynomial contrasts, e.g, -1 1 0 -2 1 1 As I understand things, the columns of x^{1:degree} are first centered and then are normalized by 1/sqrt(col sum of squares), but I can't see how to relate this to what is returned by poly(). >

Hi, I can not comprehend the linear fitting results of polynoms. For example, given the following data (representing y = x^2): > x <- 1:3 > y <- c(1, 4, 9) performing a linear fit > f <- lm(y ~ poly(x, 2)) gives weird coefficients: > coefficients(f) (Intercept) poly(x, 2)1 poly(x, 2)2 4.6666667 5.6568542 0.8164966 However the fitted() result makes sense: >

I was surprised by this (in R 2.0.1): > a <- ordered(-1:1) > a [1] -1 0 1 Levels: -1 < 0 < 1 > model.matrix(~ a) (Intercept) a.L a.Q 1 1 -7.071068e-01 0.4082483 2 1 -9.073800e-17 -0.8164966 3 1 7.071068e-01 0.4082483 attr(,"assign") [1] 0 1 1 attr(,"contrasts") attr(,"contrasts")$a [1]

Dear R-help, I'm applying the surrogate Poisson glm, by following Venables & Ripley (7.3 pp238-42). >overall_cbind(expand.grid(treatment=c("Pema","control"),age=c("young","adult","old"),repair=c("excellent","good","poor")),Fr=c(8,0,7,1,2,0,2,7,1,4,7,1, 0,3,2,5,1,9))

On 16/02/18 15:28, Bert Gunter wrote: > This is really a statistical issue. What do you think the Intercept term > represents? See ?contrasts. > > Cheers, > Bert > > > > Bert Gunter > > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom

This is really a statistical issue. What do you think the Intercept term represents? See ?contrasts. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Thu, Feb 15, 2018 at 5:27 PM, Marc Girondot via R-help < r-help at

> I am planning in doing in IR, but with target specific-passes (such as X86ExpandAtomicPass) > that just share some of the code This would more normally be done via target hooks in LLVM, though the principle is sound. > But it must be target-dependent as for example on Power a > seq_cst store has a fence before it, while on ARM it has a fence > both before and after it (per

Dear R-er, I try to get the standard error of fitted parameters for factors with a glm, even the reference one: a <- runif(100) b <- sample(x=c("0", "1", "2"), size=100, replace = TRUE) df <- data.frame(A=a, B=b, stringsAsFactors = FALSE) g <- glm(a ~ b, data=df) summary(g)$coefficients # I don't get SE for the reference factor, here 0:

In Venables \& Ripley 3rd edition (p. 231) the proportional odds model is described as: logit(p<=k) = zeta_k + eta but polr apparently thinks there is a minus in front of eta, as is apprent below. Is this a bug og a feature I have overlooked? Here is the naked code for reproduction, below the results. ------------------------------------------------------------------------ --- version

> Date: Wed, 30 Jun 1999 11:12:24 +0200 (MET DST) > From: Torsten Hothorn <hothorn at amadeus.statistik.uni-dortmund.de> > > yesterday I had a little shock using qr (or lm). having a matrix > > X <- cbind(1,diag(3)) > y <- 1:3 > > the qr.coef returns one NA (because X is singular). So I computed the > Moore-Penrose inverse of X (just from the

Hi all, What are the real technical difference between qemu-kvm and qemu-kvm-ev packages? What are the advantages to use qemu-kvm-ev (if exists someone)? Or qemu-kvm-ev makes sense when is used with ovirt only?? Thanks.

I've been inspired to look at the R source code by some strange timing results that I wrote about on my blog at radfordneal.wordpress.com (see the posts on "Speeding up parentheses..." and "Two surprising things...". I discovered that the strange speed advantage of curly brackets over parentheses is partially explained by an inefficiency in the evalList and

I have a frame which contains 3 columns: "date" "defectnum" "state" And I want to get the most recent state change for a given defect number. date is POSIXct. I have tried: aggregate(ev$date, by=list(ev$defectnum), max) Which appears to be working except that the dates seem to come back as integers (presumably the internal representation of POSIXct). When I

I see with the introduction of CentOS 7.5 there's a new qemu-kvm-ma package on ppc64le (which is actually newer than qemu-kvm-ev currently). Does anyone know what the difference is between these two packages? We currently use qemu-kvm-ev and we've run into this bug [1] which got me wondering if we should be switching to that package on ppc64le. Thanks! [1]

Since C8.1 kvm guests have a huge delay while booting on a kvm host based on C6. This delay was not present with C8.0. The "pause" happend direct after the grub step. The VNC session shows only a "_" character. Any ideas what changes? -- Leon

Hello When I read a SPSS *.por file with read.spss everything after a umlaut is missing: > library("foreign") > spssdaten <- read.spss("projets.por") > attr(spssdaten$PROJETX, "value.labels")[1:20] Bg Stammzellenforschung Bb 863 862 Bb

Hello, Sandro! On 11.05.2018 12:19, Sandro Bonazzola wrote: > Sadly, the new qemu-kvm-ev we prepared for CentOS 7.5 didn't get released ( > https://bugs.centos.org/view.php?id=14764) but the new build is ready. After installing CentOS 7.5 and installing package qemu-kvm-ev I can't install KVM on x86_64 arch: command "yum -y install perf qemu-kvm-ev qemu-kvm-tools-ev

Good day oh technical ones . I was running Samba 4 (client only, not using it as a DC so effectively running Samba 3 code from the Samba 4 tree) and, other than a little "Gotcha!" regarding decoding Kerberos PACs, it was all working perfectly. Then recently I had to upgrade, to "4.2.0pre1-GIT-b505111" (I had to upgrade the OS on the server

Hi, I am new to R. I don't have strong background of statistics. I am a student of Geotechnical Engineering. I tried to run a nonlinear regression for a three-variable function, that is N = f(CSR, ev) # N is a function of CSR and ev, and N = CSR/(A +B*CSR), wherer (A,B) are function of ev. N, CSR and ev are observed in the experiments. Following is my R script. rm(list=ls())

Hi I am trying to run CoreOS (Container Linux) as a guest OS using KVM/QEMU. One of their suggestions is to pass config info into the VM using the "fw_cfg" option . When I try this I get the error "-fw_cfg invalid option". If I run the vm with the help option it does not list the fw_cfg option. However, according to the qemu documentation, see here