search for: resids

Hi, I am trying to create 3 mds plots: one with axis 1 vs axis 2, one with axis 2 vs axis 3, and one with axis 1 vs axis 3. When inputting my code, I only end up with one diagram and when inputting mdsg.mds$dims, the program returns 2 for 2 dimensions. How can I create the other two plots? Any help would be greatly appreciated, Calla Carbone The table I use is number of each taxa on each

Hello, I?m trying out the ?resident key? functionality in OpenSSH 8.2, and I?m having trouble getting it to find keys that I?ve created. I?m trying to create a new resident key using: ssh-keygen -O resident -t ed25519-sk -f <filename> This creates a key, but I?m not actually sure it is creating a ?resident? key, as when I try to dump out the resident keys with either ?ssh-keygen -K?

Hi all Consider the family function, as used by glm. The help page says the value of the family object is a list, one element of which is the following: dev.resids function giving the deviance residuals as a function of (y, mu, wt). But reading any of the family functions (eg poisson) shows that dev.resids is a function that computes the *square* of the deviance residuals (at least, by every definition I know of). Further, the deviance residuals return...

# HG changeset patch # User Boris Ostrovsky <boris.ostrovsky@amd.com> # Date 1338309680 -7200 # Node ID 3d52d9fe62559ed6f90cb33a4b95f536ab5bc683 # Parent 53e0571f94e4bcc45270dcbd444c7c91166cef6d xenpm: Fix reporting of C0 residence times Idle state residence times as provided by pmstat_get_cx_stat() are not reported precisely since remote core may be in idle state and therefore has not

An excerpt from dataset ChickWeight: ??? weight Time Chick Diet 1?????? 42??? 0???? 1??? 1 2?????? 51??? 2???? 1??? 1 3?????? 59??? 4???? 1??? 1 I am interested in the residuals of the dataset.? Specifically in saving them to another format. I have been creating text files with sink. CW.lm <- lm(weight ~ Diet, ChickWeight) resid.CW.lm <- resid(CW.lm) But when I call: resid.CW.lm The data

...ndom intercept. The residuals output by resid had the following properties: > summary(resid(lmer1)) Min. 1st Qu. Median Mean 3rd Qu. Max. -5.92e+01 -1.29e+01 -1.10e+00 2.62e-15 1.31e+01 6.66e+01 > sd(resid(lmer1)) [1] 19.6 My naive method gave: > summary(my.resids) Min. 1st Qu. Median Mean 3rd Qu. Max. -1.84e+02 -3.81e+01 3.12e+00 -1.93e-13 4.00e+01 1.71e+02 > sd(my.resids) [1] 56.4 Both the mean and the sd are MUCH higher. All I did was use the fixed effects with random effects flattened to predict y's. Code below. Bes...

Dear all, I have three concerns: 1) I am running models with the lme4 package. I cannot find a way to pull out a vector of the fitted values and the residuals. Does anybody know how to do it? 2) How can I nest a random effect variable into a "two-level" fixed effect variable? 3) Suppose I have the following model: y = a + b|c + d + error, where 'a' is a fixed effect, 'c'

x86 pm : provide CC7/PC2 residency Sandy bridge introduces new MSR to get cc7/pc2 residency (core C-state 7/package C-state 2). Print the cc7/pc2 residency when on sandy bridge platform. Signed-off-by: Yang Zhang <yang.z.zhang@intel.com> diff -r 662dbf6ee71c tools/libxc/xc_pm.c --- a/tools/libxc/xc_pm.c Mon Oct 24 18:01:07 2011 +0100 +++ b/tools/libxc/xc_pm.c Fri Oct 28

Dear experts, I am trying to create a data frame from the residuals I get after having applied a linear regression to each column of a data frame, but I don't know how to create this data frame from the resulting list since the list has differing numbers of rows. So for example: age<- c(5,6,10,14,16,NA,18) value1<- c(30,70,40,50,NA,NA,NA) value2<- c(2,4,1,4,4,4,4) df<-

...lt;-residuals(m1) truehist(res,main="Histogram of Residuals") curve(dnorm(x,mean=mean(res),sd=sd(res)),add=TRUE) qqnorm(fitted(m1),resid(m1), ylim=range(fitted(m1)), main="QQNorm Plot") plot(residuals(m1)~fitted(m1),main="Resid vs.Fits",xlab="Fits",ylab="Resids");abline(h=0) plot(residuals(m1),type="l",main="Resid vs Order",ylab="Resids") acf(residuals(m1), main="Resid Autocorrelation") boxplot(vTotal~fCollar, data=collars,main="Box plot of Collars", ylab="No.of Prey", xlab="Collar&quot...

Hi everyone, When I set CONFIG_ACPI_PROCESSOR, CONFIG_CPU_IDLE and CONFIG_INTEL_IDLE to y then I cannot boot Xen; there is a crash. If I turn CONFIG_INTEL_IDLE off then the boot goes well and, after dom0 has booted, xenpm works and gives some sane output, see below. I have tested this with kernels 3.2 to 3.4.6. Is it impossible to use INTEL_IDLE with Xen? If this is a known issue then maybe

Hi everyone, When I set CONFIG_ACPI_PROCESSOR, CONFIG_CPU_IDLE and CONFIG_INTEL_IDLE to y then I cannot boot Xen; there is a crash. If I turn CONFIG_INTEL_IDLE off then the boot goes well and, after dom0 has booted, xenpm works and gives some sane output, see below. I have tested this with kernels 3.2 to 3.4.6. Is it impossible to use INTEL_IDLE with Xen? If this is a known issue then maybe

Hi all- this seems to be simple to figure out but since im new to writing functions I dont know what is happening. Here is my code along with the error I am receiving: semivario=function(data,ids,times,resids){ id=unique(data$ids) index=combinations(length(data$times[data$ids==id[1]]),2) time=gamma=numeric(dim(index)[1]) for (j in 1:dim(index)[1]){ time[j]=abs(data$times[data$ids==id[1]][index[j,1]]-data$times[data$ids==id[1]][index[j,2]]) gamma[j]=.5*(data$resids[data$ids==id[1]][index[j,1]]-data$res...

There may be a bug in the anova.glm function. deathstar[32] R R : Copyright 2004, The R Foundation for Statistical Computing Version 2.0.1 (2004-11-15), ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project

...y can't I just do aov(dep.var ~ indep.var, data = data.set)? What have I done to deserve this?! What gives? Am I missing something totlly obvious? R-base-1.0.0-1, linux RH 6.1. --------------------------------------------------------------------- > aov(aggr.resid ~ indiv.code, data = resids.dat) Error in lm.fit(x, y, offset = offset) : NA/NaN/Inf in foreign function call (arg 4) In addition: Warning message: "-" not meaningful for factors in: Ops.factor(y, offset) > aov(indiv.code ~ aggr.resid, data = resids.dat) Error in lm.fit(x, y, offset = offset) : NA/NaN/Inf in fo...

On Feb 17, 2020, at 9:45 PM, Damien Miller <djm at mindrot.org> wrote: > On Mon, 17 Feb 2020, Ron Frederick wrote: >> I?m trying out the ?resident key? functionality in OpenSSH 8.2, and >> I?m having trouble getting it to find keys that I?ve created. >> >> I?m trying to create a new resident key using: >> >> ssh-keygen -O resident -t ed25519-sk -f

Okay, I stumped. I'm trying to build a matrix or data.frame that consists of values by group. For example, resid, group 574 0.536196370873122 E 575 0.93191093696265 E 576 -1.27116094894117 A 577 -1.05159666055027 A 578 0.398273458301184 D 579 0.586373126102573 E 580 0.806575304513802 E 581 0.897258393118338 E 582 0.342393324256838 D 583 0.781245511773227 E I

...on isn't readily available in R's `quasi' family object, but it seems to me that the following definition could be used: }, "mu^2(1-mu)^2" = { variance <- function(mu) mu^2 * (1 - mu)^2 validmu <- function(mu) all(mu > 0) && all(mu < 1) dev.resids <- function(y, mu, wt) 2 * wt * ((2 * y - 1) * (log(ifelse(y == 0, 1, y/mu)) - log(ifelse(y == 1, 1, (1 - y)/(1 - mu)))) - 2 + y/mu + (1 - y)/(1 - mu)) I've modified the `quasi' function accordingly (into `quasi2' given below) and my results are very much in line...

Hi, among the many (5) methods that I found in the list to do partial correlation in the following two that I had a look I am getting different t-values. Does anyone have any clues on why is that? The source code is below. Thanks. pcor3 <- function (x, test = T, p = 0.05) { nvar <- ncol(x) ndata <- nrow(x) conc <- solve(cor(x)) resid.sd <- 1/sqrt(diag(conc)) pcc <-

I am now getting the occasional complaint about survival routines that are not able to handle big data.?? I looked in the manuals to try and update my understanding of max vector size, max matrix, max data set, etc; but it is either not there or I missed it (the latter more likely).?? Is it still .Machine$integer.max for everything??? Will that change??? Found where? I am going to need to go