similar to: multcomp two-way anova with interactions within and between

Hi.. i have an expression of the form: model1<-nls(y~beta1*(x1+(k1*x2)+(k1*k1*x3)+(k2*x4)+(k2*k1*x5)+(k2*k2*x6)+(k3*x7)+(k3*k4*x8)+(k3*k2*x9)+(k3*k3*x10)+ (k4*x11)+(k4*k1*x12)+(k4*k2*x13)+(k4*k3*x14)+(k4*k4*x15)+(k5*x16)+(k5*k1*x17)+(k5*k2*x18)+(k5*k3*x19)+

Hello...i want to find the empirical rate for type 1 error using fixed trimmed mean. To make it easy, i'm referring to journal given by this website http://www.academicjournals.org/ajmcsr/PDF/pdf2011/Yusof%20et%20al.pdf. I already run the programme and there is no error in it but i got zero for the empirical rate of type 1 error. The empirical rate for the type 1 error given in the journal

Hello, I haven't found errors in your code. I implemented the test in the paper (the first, fixed symetric mean) and it also gives me zero Type I errors, when alpha = 0.05. Try to see the value of min(pv) or to plot the histogram of 'pv', hist(pv) and you'll see that there are no significant p-values, at that level. Anyway I'll continue to look at it, but my first

Dear R community I currently try to get post hoc multiple comparisons with the package multcomp from a cox mixed-effects model, where the survival is explained by two variables (cover with levels: nocover and cover; treatment with levels: tx, uv, meta), whose interaction is significant. I read Hothorn, T. 2011: Additional multcomp Examples and there is an example involving a two-way ANOVA with

Hi, I have a question about how to obtain the union of several data frame rows. I'm trying to create a common key for several tests composed of different items. Here is a small scale version of the problem. These are keys for 4 different tests, not all mutually exclusive: id q1 q2 q3 q4 q5 q6 1 A C 2 B D 3 A D B 4 C D B D I would like

Here is a drop-in replacement for the R incomplete beta function. src/math/pbeta.c It is a slightly modified version of the cephes library one from Netlib. In the few cases I tried it seems to give at least 14 digit agreement with the one in S-PLUS (its hard to get more). I'm not sure what performance is like. I'd like to know if it helps with some of the problems which have been

Dear R-gurus, Just supose I have a dara.frame that looks like myDF<-read.table(stdin(),head=T,sep=",") codID,namesp,k1,k2,k3,k4 1,spA,2,5,6,3 2,spB,4,5,4,6 3,spC,2,1,5,6 4,spC,5,4,3,2 5,spD,1,2,3,4 6,spE,2,4,3,1 I need to update the columns k1-k4 with the namesp, but considering the math between Kx and codID. My desired output must looks like: codID,namesp,k1,k2,k3,k4

Hi, I'm new to R and have a problem with a little test program (see below). Why doesn't <<- in function rk4 assign the new value to y so that it is seen in rktest. I thought that <<- does exactly this. But it seems that I didn't get it right. I would be very appreciative for an explanation of that behaviour of <<-. I know how to write the whole thing so that it

I have the following matrix: > dat [,1] [,2] [,3] [,4] foo 0.7574657 0.2104075 0.02922241 0.002705617 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 foo 0.0000000 0.0000000 0.00000000 0.000000000 and given this:

Hi, I have data with binomial response variable (survival) and 2 categorical independent variables (site and treatment) (see below).? I have run a binomial GLM and found that both IVs and the interaction are significant.? Now I want to do a post-hoc test for all pairwise comparisons to see which treatment groups differ.? I tried the glht function in the multcomp package, but I get surprising

Hi, I would like to solve a system of coupled ordinary differential equations, where there is a delay (time lag) term. I would like to use the "lsoda" function "odesolve" package. However, I am not sure how to specify the delay term using the syntax allowed by odesolve. Here is an example of the kind of problem that I am trying to solve: > library(odesolve)

Hi r-users, I would like to solve system of nonlinear equation using BBsolve function and below is my code.  I have 4 parameters and I have 4 eqns. mgf_gammasum <- function(p) { t  <- rep(NA, length(p)) mn <- 142.36 vr <- 9335.69 sk <- 0.8139635 kur <- 3.252591 rh  <- 0.896 # cumulants k1 <- p[1]*(p[2]+p[3]) k2 <- p[1]*(2*p[2]*p[3]*p[4] +p[2]^2+p[3]^2) k3 <-

Dear R-helpers ? I have 7 data points that I want to fit a continuous curve to, that should look similar to a sine wave My data points would mark the local minima and maxima respectively. This is what I?ve got so far. And I would keep doing so, but sadly nls() then says that it has reached the maximum number of Iterations? ?

On Tue, 23 Jun 2015, Jakub Jelen wrote: > > On 05/29/2015 09:12 AM, Damien Miller wrote: > > Hi, > > > > OpenSSH 6.9 is almost ready for release, so we would appreciate testing > > on as many platforms and systems as possible. This release contains > > some substantial new features and a number of bugfixes. > Tested basic configuration on Fedora 22. With

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

I have just realised that I sent this to Per only. For those interested on the list: -----Original Message----- From: Gygax Lorenz FAT Sent: Tuesday, September 14, 2004 4:35 PM To: 'Per Tor??ng' Subject: RE: [R] glmmPQL and random factors Hi Per, > glmmPQL(Fruit.set~Treat1*Treat2+offset(log10(No.flowers)), > random=~1|Plot, family=poisson, data=...) > > Plot is supposed

I have tried the following code to plot and save many box plots in files. The code works by itself, but does not run in a loop. The error indicates that there is no device. The error is printed below the code. Code: for(i in 1:len) { A = as.numeric(delta[Delta[i,1]]) B = as.numeric(delta[Delta[i,2]]) C = as.numeric(delta[Delta[i,3]]) D = as.numeric(delta[Delta[i,4]]) data

Hello All, I try to use the attached code to produce a cross over plot. There are 13 subjects, 7 of them in for/sal group, and 6 of them in sal/for group. But in xyplot, all the subjects are listed in both subgraphs. Could anyone help me figure out how to get rid of the empty levels? Thanks library(lattice) pef1 <- c(310,310,370,410,250,380,330,370,310,380,290,260,90) pef2 <-

I would like to load ApoAI.RData. During the operation of reading this data an error occurs. There is also a problem with STF file. > library (limma) > load("ApoAI.RData") Warning message: 'RG' looks like a pre-2.4.0 S4 object: please recreate it > objects() [1] "RG" > names(RG) [1] "R" "G" "Rb"

Here is a little patch against 2.9p1 that performs the SNK (also known as TIS authserv) challenge-response automaticly instead of asking the user. hope you find it useful. --larry -------------- next part -------------- diff -NuBw openssh-2.9p1/Makefile.in openssh/Makefile.in --- openssh-2.9p1/Makefile.in Thu Apr 26 20:31:08 2001 +++ openssh/Makefile.in Wed Jun 6 16:15:56 2001 @@ -43,9 +43,9