similar to: some r code for linear mixed model

Dear R users: I just got confused some R code used in linear mixed model~ example,two factors,A, B,C,A is fixed ,B,C are random,and B is nested in C,if I wannt to use linear mixed model,are the following code correct for each case? case1:want to know random effect of B, case1<-lme(y~A*B*C,random=~B|C) where "B|C" stand for what?,mean B is nested in C? case2: how to wirte

hi: just a very simple quesion,how to do multiple multiplication in R x<-c(1,2,3,4,5,6) how to get 1*2*3*4*5*6? I checked the Arithmetic Operators in R,but did not found the operators for this function,anyway can do this except the loop? [[alternative HTML version deleted]]

Dear R people, I have to deal with the output of a function which comes as a matrix of vectors. You can reproduce the structure as given below: x <- list(c(1,2,4),c(1,3,5),c(0,1,0), c(1,3,6,5),c(3,4,4,4),c(0,1,0,1), c(3,7),c(1,2),c(0,1)) data <- matrix(x,byrow=TRUE,nrow=3) colnames(data) <- c("First", "Length", "Value") rownames(data)

here is the data: y<-c(5,2,3,7,9,0,1,4,5) id<-c(1,1,6,6,7,8,15,15,19) t<-c(50,56,50,56,50,50,50,60,50) table1<-data.frame(y,id,t)//longitudinal data what I want to do is to use the linear model for each id ,then get the estimate value,like: fit1<-lm(y~t,data=table1,subset=(id==1)) but ,you can see the variable "id" is quite irregular,they are not arranaged in order

All, I have just returned to R after a decade of absence, and it is good to see that R has become such a great success! I'm trying to bring Design of Experiments into some aspects of software performance evaluation, and to teach myself that, I picked up "Experiments: Planning, Analysis and Optimization" by Wu and Hamada. I try to reproduce an analysis in the book using lm, but

Hi I have a data frame with values in following format. param case1 1 a 2 b 2 c 2 d 3 e 4 f how to use aggregate so that it I only one row for each 'param' value. the output for the above input should be param case1 1 a 2 b,c,d 3 e 4 f Thanks M -- ------------- Mary

Hi, I'm trying to write a simple function like case1 <- function (m, cov, Q, R) { theta <- (acos(R/sqrt(Q^3))) beta <- (-2)*sqrt(Q)*cos(theta/3)+m[1]/3 rho1 <- (-2)*sqrt(Q)*cos((theta+2*pi)/3)+m[1]/3 rho2 <- (-2)*sqrt(Q)*cos((theta-2*pi)/3)+m[1]/3 stderrb <- deltamethod( ~(-2)*sqrt(Q)*cos(theta/3)+x1/3,m,cov) stderrr1 <- deltamethod(

Hi All, Below in my smb.conf file =================================================================== [global] netbios name = AA-FTP workgroup = airarabia realm = airarabia.com server string = Samba File Server encrypt passwords = yes security = ADS password server = 10.200.2.22 log level = 3 log file = /var/log/samba/%m.log

Hi all, I'm building a plot of the values in tmeant (below) against positions 1 to 5, using matplot. tmeant looks like this: case1 case2 pos1 861.8466 818.5909 pos2 961.2841 976.3466 pos3 878.6080 1262.8523 pos4 950.8011 1129.6080 pos5 968.1080 1063.3920 I also have lower (object tl) and upper (object tu) bounds on the confidence intervals as follows: tl: pos1

Sadly, we have discovered another line level interrupt race condition in Xen-4.1. The result was that an outstanding un-eoi''d interrupt at the IO-APIC resulted in the mptsas controller offlining the root filesystem. This is now two separate IO-APIC bugs found recently. 1) Cisco C210 M2 server - EOI Broadcast Suppression, io_apci_ack=old 2) Dell R710 - No EOI Broadcast Suppression,

Hi All. I have R code whose functionality is being replicated within a C+ program. The outputs are to be compared to validate the conversion somewhat - however (as is always the case) I have stuffed my code with random number calls. Random uniform numbers in C+ are being produced using the (Boost) mersenne-twister generators (mt11213b & mt19937) - which is the default type of generator

I''m a newbie and I''ve been trying to figure this out for a little while now, hopefully someone can point me in the right direction. case1 <div id="new"> </div> case2 <div id="new"><div id="item1"></div></div> <div id="new2"><div id="item1"></div></div> With RJS in

here is the data: y<-c(5,2,3,7,9,0,1,4,5) id<-c(1,1,6,6,7,8,15,15,19) t<-c(50,56,50,56,50,50,50,60,50) table1<-data.frame(y,id,t)//longitudinal data the above is only part of data. what I want to do is to use the linear model for each id ,then get the estimate value,like: fit1<-lm(y~t,data=table1,subset=(id==1)) but ,you can see the variable "id" is quite

Hi all, I am trying to make a script that prints all possible models from a model I've created using nls(). It is a logisitc model which in total includes 13 variables. So its >8000 models I need to create, which I don't want to do manually. I've tried modify scripts made for linear models with no results. I've tried these scripts on a two variable model (c,a1 and a2 is what I

Hi, I came into a crash when using 32-bit `speexdec` and found that there's an address overflow in function `print_comments()`: static void print_comments(char *comments, int length) { char *c=comments; int len, i, nb_fields; char *end; if (length<8) { fprintf (stderr, "Invalid/corrupted comments\n"); return; } end = c+length;

Hi, all When compiling a program with -g -O0, and if we have a PC, then with addr2line, we can get the line number of the instruction. My quesions are: what is the result of Phi node instruction, can we get the similar results ? -- Best Regards! Eric Lew -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hello, I've some problem with the ggplot2. Here's a small example: --8<-- library(ggplot2) molten <- data.frame(date=c('01','01','01','01', '02','02','02','02'), channel=c('red','red','blue','blue',

Pointers are unsigned so this shouldn't be an issue. I suspect you're being hit by something else. That or your compiler is really broken. Cheers, Jean-Marc On 02/09/2018 04:42 AM, Ruikai Liu wrote: > Hi, > > I came into a crash when using 32-bit `speexdec` and found that there's > an address overflow in function `print_comments()`: > >

I am having trouble figuring out the right form for the nlme arguments. I do have examples in Modern and Applied Statistics with S and from other sources, but I still can't figure it out. I am trying to estimate species richness (sr) in streams across minnesota. My predictor variables are depth (d), habitat diversity (habdiv), drainage area (da) and an indicator variable representing the

Dear friends. I use nls() and encounter the following puzzling problem: I have a function f(a,b,c,x), I have a data vector of x and a vectory y of realized value of f. Case1 I tried to estimate c with (a=0.3, b=0.5) fixed: nls(y~f(a,b,c,x), control=list(maxiter = 100000, minFactor=0.5 ^2048),start=list(c=0.5)). The error message is: "number of iterations exceeded maximum of