similar to: Means from balanced incomplete block design

The syntax below works, and gives the expected results, in R version 2.0.0, provided that I have loaded packages Matrix, latticeExtra and lme4. However, I cannot get it to work in version 2.2.1. Can anyone tell me how to fit this model in the more recent version? Thanks in anticipation, Nick Galwey barleyprogeny.model1lme <- lme(yield_g_m2 ~ 1, data =

Hi Ppl I have 5 adsl lines that after reading quite a bit i managed to get load balanced now abvoiusly it doesnt load balance evenly and this works on what routes are still in the routing cache. my question is my outbound masquerading had to be modified to use snat in iptables instead of just plain masquerading my outbound masquerading now works but my inbound port forwarding doesnt work would

I want to specify two factors and their interaction as random effects using the function lme(). This works okay when I specify these terms using the function Error() within the function aov(), but I can't get the same model fitted using lme(). The code below illustrates the problem. a <- factor(rep(c(1:3), each = 27)) b <- factor(rep(rep(c(1:3), each = 9), times = 3)) c <-

Dears, I'm trying to find the parameters (a,b, ... l) that optimize the function (Model) described below. 1) How can I set some constraints with MLE2 function? I want to set p1>0, p2>0, p3>0, p1>p3. 2) The code is giving the following warning. Warning: optimization did not converge (code 1) How can I solve this problem? Can someone help me? M <- 14 Y = c(0, 1, 0, 0, 0,

Dear list, I have been struggling for some time now with this code... I have this vector of unique ID "EID" of length 821 extracted from one of my dataframe (skate). It looks like this: > head(skate$EID) [1] "896-19" "895-8" "899-1" "899-5" "899-8" "895-7" I would like to remove the complete rows in another dataframe

In the output of the code below, I want to do the following: - get hats over some of the betas - get the polygons stippled, not coloured grey - remove the tick marks at the ends of the axes. If I put tick = false, the whole axis disappears. betahat <- c(0.04*0:150) betahatdens <- dnorm(betahat, 3, 1) plot(betahat, betahatdens, xlim = c(-0.2, 6.2),

At 07:12 AM 10-10-00 +0100, Prof Brian D Ripley wrote: >On Tue, 10 Oct 2000, Murray Jorgensen wrote: > >> Excuse me everyone, but I don't have to teach this very often! >> >> Has anyone got some R code for doing adjusted treatment means and the >> recovery of inter-block information in the analysis of balanced incomplete >> block designs? > >Do you

Hi, I've noticed that LLVM tends to generate suboptimal code and spill an excessive amount of registers in large functions, such as in those that are automatically generated by FFTW. LLVM generates good code for a function that computes an 8-point complex FFT, but from 16-point upwards, icc or gcc generates much better code. Here is an example of a sequence of instructions from a 32-point

Hello. I'd like to compute the associate vector of distances between leaves in a binary non-rooted tree. The definition of a distance between two leaves in a binary non-rooted tree is the number of edges in the path joining the two leaves. I've tried the ape package but I'm unable to find this vector. For example, using rtree(5,rooted=F) I've obtained the following tree: $edge

# read.table is NOT part of the data.table package #library(data.table) DFM <- read.table( text= 'obs start end 1 2/1/2015 1/1/2017 2 4/11/2010 1/1/2011 3 1/4/2006 5/3/2007 4 10/1/2007 1/1/2008 5 6/1/2011 1/1/2012 6 10/5/2004 12/1/2004 ',header = TRUE, stringsAsFactors = FALSE) # cleaner way to compute D DFM$start <- as.Date( DFM$start, format="%m/%d/%Y" ) DFM$end

Ii is difficult to provide useful help, because you have failed to read and follow the posting guide. In particular: 1. Plain text, not HTML. 2. Use dput() or provide code to create your example. Text printouts such as that which you gave require some work to wrangle into into an example that we can test. Specifically: 3. Have you gone through any R tutorials?-- it sure doesn't look like

Since the number of choices is small (6), how about this? Starting with Jeff's initial DFM: DFM <- structure(list(obs = 1:6, start = structure(c(16467, 14710, 13152, 13787, 15126, 12696), class = "Date"), end = structure(c(17167, 14975, 13636, 13879, 15340, 12753), class = "Date"), D = c(700, 265, 484, 92, 214, 57), bin = structure(c(6L, 3L, 5L, 1L, 3L, 1L), .Label

Hi all, I have a data set with time interval and depending on the interval I want to create 5 more variables . Sample data below obs, Start, End 1,2/1/2015, 1/1/2017 2,4/11/2010, 1/1/2011 3,1/4/2006, 5/3/2007 4,10/1/2007, 1/1/2008 5,6/1/2011, 1/1/2012 6,10/15/2004,12/1/2004 First, I want get interval between the start date and end dates (End-start). obs, Start , end, datediff

I come across a situation that I am having a hard time to understand. When I compile the following code : char *tst( char *dest, const char *src, unsigned int len ) { for (int i=0 ; i<len ; i++) { dest[i] = src[i]; } return dest; } Clang generates this for the ‘for’ body: for.body: ; preds = %for.cond %arrayidx = getelementptr inbounds i8,

Hello, I've been redirected from cfe-dev, as code optimizations in clang are done in llvm layer. I'm investigating how optimized code clang generates, and have come across such an example: I have two procedures: void exec0(const int *X, const int *Y, int *res, const int N) { int t1[N],t2[N],t3[N],t4[N],t5[N],t6[N]; for(int i = 0; i < N; i++) { t1[i] = X[i]+Y[i];

(I'm sending to r-bugs because rpart is one of the recommended packages and is always installed. I'm also sending it directly to Dr. Ripley, as the maintainer.) rpart working as a classifier does not work (produces no splits) when the class indicator has no instances of one of the factor levels, as long as the factor level is not the final level. I have at least a partial fix, which I

Thank you all for the useful suggestion. I did some of my homework. library(data.table) DFM <- read.table(header=TRUE, text='obs start end 1 2/1/2015 1/1/2017 2 4/11/2010 1/1/2011 3 1/4/2006 5/3/2007 4 10/1/2007 1/1/2008 5 6/1/2011 1/1/2012 6 10/5/2004 12/1/2004',stringsAsFactors = FALSE) DFM DFM$D =as.numeric(difftime(as.Date(DFM$end,format="%m/%d/%Y"),

Thank you Jeff and All, Within a given time period (say 700 days, from the start day), I am expecting measurements taken at each time interval;. In this case "0" means measurement taken, "1" not taken (stopped or opted out and " -1" don't consider that time period for that individual. This will be compared with the actual measurements taken (Observed-

Hey, I''m trying to set up a Gentoo box to replace an aging BSD box here. The BSD box is running packet filter and I have it set up to take all data and route it to one of six sattelites. I have come up with the following config, but unfortunately I have no real way to test it short of switching the satellites over to the new system and prayer. The setup is: 192.168.252/22 - The LAN

Hi all, I hope that there might be some statistician out there to help me for a possible explanation for the following simple question. Y1~ lm(y~ t1 + t2 + t3 + t4 + t5,data=temp) # oridnary linear model library(gam) Y2~ gam(y~ lo(t1) +lo(t2) +lo(t3) +lo(t4) +lo(t5),data=temp) # additive model In the first model t1, t2 and t3 found to be significant,. However, in the second model (using