similar to: Trouble phrasing an R command that will run the model i need (ANOVA, nes

Hi, I have been trying to find the appropriate R command to analyse my datasets according to a particular model. Unfortunately, my best attempts at doing so have so far not worked. I am wondering if anybody can help me to figure out what i've been doing wrong, and what i need to do in order to use R correctly? The model is an ANOVA with some crossed factors, interactions, and one nested

Thank you for the suggestion, Bill. The result is not quite what I would like. Here's sample code for you or anyone else who may be interested: Al1 = c('A','C','C','C') Al2 = c('G','G','G','T') Freq1 = c(0.0078,0.0567,0.9434,0.9908) MAF = c(0.0078,0.0567,0.0566,0.0092) m1 = data.frame(Al1=Al1,

Hey, I have a dataset and I want to identify the records by groups for further use in ggplot. Here is a sample data: ID Value AL1 1 AL2 2 CA1 3 CA4 4 I want to identify all the records that in the same state (AL1 AND A2), group them as "AL", and do the same for CA1 and CA4. How can I have an output like: ID Value State AL1 1 AL AL2 2 AL CA1 3 CA CA4 4

I am new in R and i am having trouble here. I?ve already searched in the list but hasn?t helped When i run this script above i get the message "Error in gen[j, i] : incorrect number of dimensions". However gen is 1000x200 (ind x loc) and so is g could anybody help me for (i in 1 : loc) { #loc=200 for (j in 1 : ind) { #ind=1000 g1 <= function ( gen ) matrix ( if (gen[j, i]

Hello, All! How might one accomplish this using the by() function? m1 is a data frame. # populate column "m1$major_allele" for ( i in 1:length(m1$major_allele)) { if ( m1$Freq1[i] == m1$MAF[i]){ m1$major_allele[i] = m1$Al1[i] } else{ m1$major_allele[i] = m1$Al2[i] } } Jim [[alternative HTML version deleted]]

Good Mourning, I have a function to generate a matrix as I show part of it; g[j,i]<-if (gen[j,i]==0) al1[i,1]+al1[i,1] else ... However i would like that this function occurred with a probability P and that another function (another formula to generate g matrix) with probability P-1 That?s it, if P is .7, i would like that in 70% of the times (for random i and j) the matrix g was generated

Hi all: I've got some core dumps with chan_skinny. The client is ATA186 with v2.16.1.ms ata18x (Build 030814a). The * version is CVS-10/05/03-16:03:26. When I make a call, the phone connected with ATA rings only 1 time and * dies. Maybe I have some errores in ATA config. If someone has proven configs for ATA, please send me the details. Thanks in advance, Gus The logs: *CLI> Version

Here is what I am attempting to do (which works well on Cisco Call Manger). I have some 7960's that have multiple lines on them. The second line specifically is a "helpdesk" line that is shared among multiple phones. Here is how I am making that line ring on multiple phones, maybe you have other suggestions: exten => 135,1,Dial(SIP/135@100&SIP/135@101,20,rt) So this

Is there a way to combine two columns within a data frame? Example data: id snp AL1 AL2 1500 30 A B 1510 30 A A 1520 30 A B This is what I would like: indv snp AL1AL2 1500 30 AB 1510 30 AA 1520 30 AB Any help is greatly appreciated. Alysta

Hello All, I have a toy dataframe like this. It has 8 columns separated by tab. Name SampleID Al1 Al2 X Y R Th rs191191 A1 A B 0.999 0.09 0.78 0.090 abc928291 A1 B J 0.3838 0.3839 0.028 0.888 abcnab A1 H K 0.3939 0.939 0.3939 0.77 rx82922 B1 J K 0.3838 0.393

I could use some skinny/Cisco help here. Was finally able to get the phone registered to * but whenever someone tries to call that phone it freezes and reboots itself. Same thing happens when you pick the handset up off the 7960G; it locks and reboots about 5 sec later. Here is what * shows when I plug the phone in: -- Starting Skinny session from 64.72.107.1 Device SEP000F3442E4A7 is

I am trying to use multcomp to do a Tukey posthoc on growth increments among genetic crosstypes. #Fixed effect model m1 <- lm(inc ~ 0 + Age+ Crosstype + Sex, data = Data.age) summary(m1) RESULTS of the model: summary(m1) Call: lm(formula = inc ~ 0 + Age + Crosstype + Sex, data = Data.age) Residuals: Min 1Q Median 3Q Max -0.87180 -0.34002 -0.02702 0.27710 2.17820

Greetings: I would like comments on this example and after fixing it up, I need help from someone who has access to insert this in R's help page for plotmath. I uploaded a drawing http://pj.freefaculty.org/R/Normal-2009.pdf that is created by the following code http://pj.freefaculty.org/R/Normal1_2009_plotmathExample.R This will be a good addition to the plotmath help page/example.

R for OS X, version 2.0.1 Has the add parameter of plot commands been deprecated? It no longer occurs in the help listing for plot, and doesn't work, either. If it has been deprecated, what is the replacement? That is, how does one overlay an existing plot? -- John R. Vokey, PhD Professor B.E.R.G. - Behaviour and Evolution Research Group Micro-Cognition Laboratory Department of

useRs, A no doubt simple question, but I am baffled. Indeed, I think I once knew the answer, but can't recover it. The default contrasts for aov (and lm, and...) are contr.treatment and contr.poly for unordered and ordered factors, respectively. But, how does one invoke the latter? That is, in a data.frame, how does one indicate that a factor is an *ordered* factor such that

guRus and useRs, As I instruct my students: "With R what is difficult in anything else, is easy, usually one line of code; but, what is easy in anything else, is *&^%$%#$... (translation: next to impossible) in R." I just ran into such a case that has, to put it mildly, driven me to use spreadsheets (if that is not a sign of complete desperation, I don't know what is).

Caveat: I've only played with this a couple of years ago... I believe you can just add each host _twice_ (or as many times as the number of CPUs at that host) to get both CPUs to work. Andy From: Paul Y. Peng > > Hi, > > does anybody know how to use the dual processors in the > machines of a cluster? I am using R with rpvm and snow > packages. I usually start pvm

The following dummy data frame has factor Q (with 2 levels) nesting factor P (with levels p1 and p2 nested under q1, and p3 and p4 nested under q2), but both crossing the random variate s, which has 8 levels. The dependent measure is dv. > # The data frame: > testnest dv s P Q 1 1 s1 p1 q1 2 2 s2 p1 q1 3 1 s3 p1 q1 4 2 s4 p1 q1 5 1 s5 p1 q1 6 3 s6 p1 q1 7 3 s7

I want to shade the area under the curve of the standard normal density. Specifically color to the left of -2 and on. How might i go about doing this? Thanks -- View this message in context: http://n4.nabble.com/Shade-area-under-curve-tp1586439p1586439.html Sent from the R help mailing list archive at Nabble.com.

HelpeRs, I have what amounts to a stupid design---entirely my fault, but it seemed like a good idea at the time. Every participant in the experiment receives a series of a two-alternative forced-choice (2afc) pairs generated at random from a pool of items that make up the pairs. The independent variable of interest is the difference in the 2afc pairs on a metric measure to predict