similar to: apply question

Dear R-help list, Sorry to trouble everyone. This seems like it could be achieved with a single command (? variant of apply), but I am not quite seeing it. I am trying to multiply one vector (a1 below) by corresponding values in a3 (as determined by matching element in a vector a2). The example below might be clearer. a1 <- c(4,3,4,6,8,9,2,3,4,6,7,4) a2 <-

I am new to R. I just tried to recreate in R (using sem package and the identical input data) a solution for a simple measurment model I have found before in LISREL. LISREL had no problems and converged in just 3 iterations. In sem, I got no solution, just the warning message: "Could not compute QR decomposition of Hessian. Optimization probably did not converge. in: sem.default(ram =

Hello, I finally run my measurement model in sem - successfully. Now, I am trying to print out the path diagram that is based on the results - but for some reason it's not working. Below is my script - but the problem is probably in my very last line: # ANALYSIS OF ANXIETY, DEPRESSION, AND FEAR - LISREL P.31 library(sem) # Creating the ANXIETY, DEPRESSION, AND FEAR intercorrelation matrix

Hi, I'm trying to conduct sensitivity analysis in R using the 'sensitivity' package. Although the description of functions seem straightforward, I can?t succeed. The definition of input factors can be the problem. library(sensitivity) #A simple model with 4 input factor to test the morris function: model01=function(a1,a2,a3,a4) { Z<-numeric(10) Z[1]<-runif(1)

Hello. This is a follow-up to a question I posted last week. With some previous suggestions from the R-help community, I have been able to plot survival (, hazard, and density) curves using published data for Siler hazard parameters from a number of ethnographic populations. Can the function below be modified, perhaps with a "for" statement, so that multiple curves (different line

#I have a data set that looks like this. A bit more complicated actually with # three factor levels but these calculations need to be done on one factor at a #I then have a set of different rates that are applied #to it. #dataset cata <- c( 1,1,6,1,1,2) catb <- c( 1,2,3,4,5,6) doga <- c(3,5,3,6,4, 0) data1 <- data.frame(cata, catb, doga) rm(cata,catb,doga) data1 # start rates #

Dear people from the R help list, I have a question that I can't get my head around to start answering, that is why I am writing to the list. I have data in a format like this (tabs might look weird): John A1 1 0 1 John A2 1 1 1 John A3 1 0 0 Mary A1 1 0 1 Mary A2 0 0 1 Mary A3 1 1 0 Peter A1 1

Dear R users, I have a data where I desire to subset according to certain conditions. However, the script is very messy as there are about 30 distinct conditions. (i.e. same script but with different conditions) I would like to make a user defined function so that I can input the desired conditions and just get the results accordingly. Below is an arbitrary data set & sample statements

Dear R users, Basically, from the following arbitrary data set: a <- data.frame(id=c(c("A1","A2","A3","A4","A5"),c("A3","A2","A3","A4","A5")),loc=c("B1","B2","B3","B4","B5"),clm=c(rep(("General"),6),rep("Life",4))) > a

Dear all, Is it possible to incorporate a nested design in GEE? I have measurements on trees that where measured in two years. The trees are nested in plots. Each plot contains 24 trees. The number of plots is 72. Hence we would expect 2 * 24 * 72 = 3456 data points. A few are missing, so we end up wih 3431 data points. This is what I have tried until now. #assuming independence between trees

Hello. I am trying to write an R function to plot the survival function (and associated hazard and density) for a Siler competing hazards model. This model is similar to the Gompertz-Makeham, with the addition of a juvenile component that includes two parameters---one that describes the initial infant mortality rate, and a negative exponential that describes typical mortality decline over the

I want to do something like this in R. If I have three vectors > a1 [1] 1 2 3 > a2 [1] 4 5 6 > a3 [1] 9 10 7 I want to compute 1. A vector that is the mean at each serial position of a1, a2, and a3. so in this example it would have the contents 4.667, 5.667, 5.333333 2. A vector that is the SD at each serial position of a1, a2, and a3. so in this example it would have the contents

Dear User, thank for the attention. I have a data.frame with 5 columns (ex:ID, a1,a2,a3,a4) and 1000 rows. I wish to find the absolute max value for all data.frame and save a new data.frame with the row where is that value. Ex: ID: 1,2,3,4,5,6,7,8,9,10 a1:1,2,3,4,5,6,7,8,9,10 a2:11,12,13,14,15,16,17,18,19,20 a3:21,22,23,24,25,26,27,28,29,30 a4:31,32,33,34,35,36,37,38,39,40 The

Hi, It's nice to be able to define S4 classes with slots that correspond to standard attributes: setClass("A1", slots=c(names="character")) setClass("A2", slots=c(dim="integer")) setClass("A3", slots=c(dimnames="list")) By doing this, one gets a few methods for free: a1 <- new("A1", names=letters[1:3])

I have design with two repeated-measures factor, and no grouping factor. I can analyze the dataset successfully in other software, including my legacy DOS version BMDP, and R's 'aov' function. I would like to use 'Anova' in 'car' in order to obtain the sphericity tests and the H-F corrected p-values. I do not believe the data are truly deficient in rank. I

Hi, I know we can use 1:10 to represent the 1,2,3,...,10 numbers, but the following conditions are except. Anybody knows how to represent the following two cases with similar usage of ":" or others? Usually, i will get several hundred names for them, such as a1,a2,... or f[[1]],f[[2]],... #Example data a1<-array(1:12,c(2,3,2)); a2<-array(2,c(2,3,2)); a3<-array(0,c(2,3,2))

Hello, I'm new in R and I want to do one thing that is very easy in excel, however, I cant do it in R. Suppose we have the data frame: data<- data.frame(A=c("a1","a2","a3","a4","a5")) I need to obtain another column in the same data frame (lets say B=c(b1,b2,b3,b4,b5) in the following way: b1=a1/(a1+a2+a3+a4+a5)

Dear sir, I have a matrix like a<-matrix(c(0,2,0,4,0,6,5,8,0),nrow=3) colnames(a)<-c("F1","F2","F3") rownames(a)<-c("A1","A2","A3") a F1 F2 F3 A1 0 4 5 A2 2 0 8 A3 0 6 0 I want to extract all pairs (rownames, columnames) from which the value in the matrix is 0 The result should be something like this A1, F1 A2,

Dear list members, I want to draw surfaces of Dirichlet distributions with different parameter settings. My code is the following: #<begin code> a1 <- a2 <- a3 <- 2 #a2 <- .5 #a3 <- .5 x1 <- x2 <- seq(0.01, .99, by=.01) f <- function(x1, x2){ term1 <- gamma(a1+a2+a3)/(gamma(a1)*gamma(a2)*gamma(a3)) term2 <- x1^(a1-1)*x2^(a2-1)*(1-x1-x2)^(a3-1)

Hi everyone, I have two columns: ? ?A? ? ? ? ? ? ? ?B ? ?1? ? ? ? ? ? ? ?1? ?1? ? ? ? ? ? ? ?0 ? ?0? ? ? ? ? ? ? ?1 ? ?0? ? ? ? ? ? ? ?0 I have 4 categories which are: 1) if A = 1 and B =1 then A1 = 1, else A2 = 0, A3 = 0, A4 = 0 2) if A = 1 and B =0 then A1 = 0, else A2 =1, A3 = 0, A4 = 0 3) if A = 0 and B = 1 then A1 = 0, else A2 = 0, A3 = 1, A4 = 0 4) if A = 0 and B =0 then A1 = 0, else A2 =