similar to: two-factor linear models with missing cells

I'm having problems with environments and update() that I expect have a simple explanation. To illustrate, suppose I wanted to make a very primitive Tukey one-degree-of- freedom for nonadditivity test and naively wrote: nonadd <- function(formula){ f <- lm(formula) v <- f$fitted.values^2 g <- update(f, . ~ . + v) anova(f,g) } x <-

Dear R-helpers, I'm running Sweave() on a file. First run: > Sweave('20080331.Rnw') Writing to file 20080331.tex Processing code chunks ... 1 : term hide (label=setup) 2 : echo term verbatim (label=oatvar) 3 : echo term verbatim (label=oatvar1) 4 : echo term verbatim (label=oat2wt) 5 : echo term verbatim (label=oat2wt) 6 : echo term verbatim (label=lm) 7 : echo term

Hi, i have atwo node HA-cluster with pacemaker, corosync, libvirt and KVM. Recently i configured a new VirtualDomain which runs fine, but live Migration does not succeed. This is the error: VirtualDomain(vm_snipanalysis)[14322]: 2019/09/18_16:56:54 ERROR: snipanalysis: live migration to ha-idg-2 failed: 1 Sep 18 16:56:54 [6970] ha-idg-1 lrmd: notice: operation_finished:

Hi. I install from source a wine 20090914. I have problem with printers. I have a cups printers in the system. When i open a Word it see a printers in the print box I can choise right one and I can see how it send task to the printer, but this is never print. I check the localhost:631 jobs and I don't see any task from wine, tahat I just send to the printer. In howto I found that cups

Dear R-helpers, I'm stuck with a little problem that surely has an easy solution but I can't think of a way to solve it. I'd really appreciate any help you can offer me! I'll provide a small example. Given a dataframe data.txt that looks like this: ID freq Var Var_mean Ratio_mean Var_median Ratio_median Var_sum Ratio_min Var_max Ratio_max Var_min

Dear all, The 'make check' step fails for the pacakge mva on IBM AIX. The tail of the Rout log file looks like: > for(factors in 2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166

Hi R bayesians, I need an advise how to resolve the two different estimates applying a traditional glm (TG) and a bayes glm (BG), and different results depending on the data formats of response data and the prior specs using bayesglm in R. I'm not familiar with bayes estimate and my colleague asked me to look into this because the EPA from France reported a quite different estimates for

I am using an example posted in this help forum to work with a file. the head of the file looks like: 988887 2007-03-05 2007-06-01 90 3 5.450 205500.00 999.00 999.000 0.000 0 0 988887 2007-03-06 2007-06-01 90 3 5.450 205500.00 999.00 999.000 0.000 1 0 988887 2007-03-07 2007-06-01 90 3 5.450 205500.00 999.00 999.000 -0.100 2 0 988887 2007-03-08 2007-06-01 90 3 5.450 205500.00 999.00 999.000 -0.100

Hey everyone, Logwatch flagged something in my Apache logs, and it says it was a possible successful probe. Hmmm. Here's what it says: --------------------- httpd Begin ------------------------ A total of 1 sites probed the server 66.249.137.70 A total of 2 possible successful probes were detected (the following URLs contain strings that match one or more of a listing of

Dear All, In R 3.4.2 (Linux), the compiler seems to have regressed: $ R --vanilla g = function() { N = 1e7; ans = numeric(N) system.time({for (j in 1:N) ans[j] = 1}) } g() # user system elapsed # 4.272 0.000 4.272 g1 = compiler::cmpfun(g) g1() # user system elapsed # 4.232 0.004 4.235 Running the above code in Windows 3.3.1, g() takes the same time, but g1() takes around 0.5

I have the following: Time A1 A1 B1 B1 C1 C2 x y x y x y 0 5 6 6 7 7 9 1 3 4 4 3 9 9 2 5 2 6 4 7 4 I want to change it to the following: 0 1 2 x y x y x y A1 5 6 3 4 5 2 B1

Dear All: In the attached file, I have 3 group patients, and there are 5 in each group (the groups are decided by the prefix of the idno). I want draw a repeat measurement comparison figure. My goal is to list 5 patients from same group on one horizontal line. But xyplot sounds pick them randomly (or I was confused?). Could you please help me modify the following code to accomplish this?

Dear R fans, I would like to create a scatterplot showing the relationship between 4 continuous variables. I thought of using the package "scatterplot 3d" to have a 3-dimensional plot and then using the size of the symbols to represent the 4th variable. Does anybody know how to do this? I already tried to create this graph using the colour of the symbols, but I was unable to generate

Hi I have a set of data with both quantitative and categorical predictors. After scaling of response variable, i looked for multicollinearity (VIF values) among the predictors and removed the predictors who were hinding some of the other significant predictors. I'm curious to know whether the predictors (who are not significant) while doing simple 'lm' will be involved in

Hi R-users, I would like to calculate weighted mean of several variables by two factors where the weight vector is the same for all variables. Below, there is a simple example where I have only two variables: "v1","v2" both weighted by "wt" and my factors are "gender" and "year". set.seed(1) df <- data.frame(gender = rep(c("M",

Hi I have a set of data with both quantitative and categorical predictors. After scaling of response variable, i looked for multicollinearity (VIF values) among the predictors and removed the predictors who were hinding some of the other significant predictors. I'm curious to know whether the predictors (who are not significant) while doing simple 'lm' will be involved in

Dear Experts, I am new to R and unfortunately cannot start with a simply statistical analysis: I manually determined the volume of the right and left hippocampus in a group of meditators and in a group of controls. My data-sheet looks as follows: observation subject group age gender hemisphere volume 1 am04 m 25 f left 3.637 2 am04 m 25 f right 3.713 3 ao08 m 47 m left 3.715 4 ao08 m 47

Dear all I need to compute percentage changes of my data, but unfortunately they contain both negative and zero values, and I am quite confused on how to proceed. Searching the internet I found that many people ran into similar issues, with no obvious solution available. The last couple of weeks I've been playing with all the data transformations that I could think of. Below I will expose on

Dear list, if I do smooth.spline(tmpSec, tmpT, all.knots=T) with the attached data, I get this error-message: Error in smooth.spline(tmpSec, tmpT, all.knots = T) : smoothing parameter value too small If I do smooth.spline(tmpSec[-single arbitrary number], tmpT[-single arbitrary number], all.knots=T) it works! I just don't see it. It works for hundrets other datasets, but not for

Dear All: Could you please tell me how I can draw figure formatted like figure 4.18 of MASS (4th) with the attached data set? Thanks Zhongming Yang --------------------------------- -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: sample.txt Url: https://stat.ethz.ch/pipermail/r-help/attachments/20050316/abfdb85e/sample.txt