similar to: how to simulate from a conditional distribution

Hello all I have a feeling this is very simple......but I am not sure how to do it My boss has two variables, one is an average of 4 numbers, the other is an average of 3 of those numbers i.e var1 = (X1 + X2 + X3 + X4)/4 var2 = (X1 + X2 + X3)/3 all of the X variables are supposed to be measuring similar constructs not surprisingly, these are highly correlated (r = .98), the question is how

Hallo Is there an elegant way to do the following: Dataset consists of 2 variables: var1: some measurements, and var2: a grouping variable with two values, 1 and 2. There are (say) 10 measurements from group 1 and 15 measurements from group 2. The idea is to study the permutation distribution of mean(group 1) * mean(group2). One way would be to permute 1s and 2s and select the corresponding

Dear list, I have been trying to use coxme in R 2.3.1. When I use coxme in the following data sim.fr1, i get "Warning messages: using 'as.environment(NULL)' is deprecated" Why does it occur? How can I hide such warning message, especially when coxme is under a loop? Mohammad Ehsanul Karim (Institute of Statistical Research and Training, University of Dhaka) >

Hi :-) I'm new to R and I started using it for a project (I'm the CS guy in a group of statisticians helping them find out how to solve issues as they come out). This is my first post to the list and I am starting to learn R. Well, they were used to doing MCA analysis in other programs where the data seems to be preprocessed automatically before running MCA. So, they need to process a

I need to do a somewhat complex rearrangement of an existing dataframe that involves an "on-the-fly" conditional summary as well. I've tried to make the example as simple as possible. Code to produce the object being acted on is at the end of the message. I hope this isn't too much for a single posting. Any guidance will be much appreciated. The input example looks like

Dear all, Y, X are bivariate normal with all the parameters known. I would like to generate numbers from the distribution Y | X > c where c is a constant. Does there exist an R function generating random numbers from such a distribution? Thank you very much. hannah [[alternative HTML version deleted]]

Hello everyone, I am looking at the joint spatial distribution of 2 kinds of organisms (estimated on a grid of points) and want to test for significant association or dissociation. My first question is: do you know a nice technique to do that, considering that I have a limited number of points (36) but that they are repeated (4 times)? I did GLMs to test for correlations between the

Dear List, Trying to explain my situation as simply as possible for me: I am running a series of iteration on coxph model on simulated data (newly generated data on each iteration to run under coxph; in my example below- sim.fr is the generated data). However, sometimes i get warning messages like "Ran out of iterations and did not converge" or "Error in var(x, na.rm = na.rm) :

Hi Folks, I'm wondering if there's a secret trick to achieve the following. I have some big code for analysis related to a named variable, which will be one of several in the columns of a dataframe, and I would like to be able to choose between a run for just one of these variables, or a run which loops over them all. So, for a single run, I could have the following kind of thing in a

Hello, I am performing a sensitivity analysis using a Latin Hypercube sampling. However, I have difficulty to draw a Hypercube sample for one variable. I?ve generated this variable from a Poisson distribution as follows: set.seed(5) mortality_probability <- round(ppois(seq(0, 7, by = 1), lambda = 0.9), 2) barplot(mortality_probability, names.arg = seq(0, 7, by = 1), xlab = "Age

Hi, I am using R 1.9.1 on on i686 PC with SuSE Linux 9.0. I have a data.frame, e.g.: > myData <- data.frame( var1 = c( 1:4 ), var2 = c (5:8 ) ) If I add a new column by > myData$var3 <- myData[ , "var1" ] + myData[ , "var2" ] everything is fine, but if I omit the commas: > myData$var4 <- myData[ "var1" ] + myData[ "var2" ] the name

Hi, anybody have any ideas on this ? I have two sequences of proportions. Due to conventions in my field, I need to produce a linear correlation between the two. Each sequence of proportions are based upon differing numbers of observations (although within a sequence the number of observations may not fluctuate too much) so it may be necessary/advisable to variance stabilize. Is their a best

Hi all, I have been trying to solve this problem and have had no luck so far. I have numeric vectors VAR1, VAR2, and VAR3 which I am trying to cbind. I also have a character vector "VAR1,VAR2,VAR3". How do I manipulate this character vector such that I can input a transformed version of the character vector into cbind and have it recognize that I'm trying to refer to my numeric

Dear List, I have Multi-level Data i= Indivitual Level g= Group Level var1= First Variable of interest var2= Second Variable of interest and I want to count the frequency of "var1" and "var2" on the group level. I found a way, but there must be a much simpler way. data.ml <- data.frame(i=c(1:8),g=as.factor(c(1,1,1,2,2,3,3,3)),var1=c(3,3,3,4,4,4,4 ,4),

Buenos días. Hoy ando un poco (o bastante) espeso y no doy con la tecla de una cosa que seguro que es muy simple.. Pongo un ejemplo. var1 <- c(rep(0,3),rep(1,2)) var2 <- c(rep(1,2),0,0,1) var3 <- c(rep(1,2),rep(0,3)) var4 <- c(rep(1,2),rep(0,3)) datos <- data.frame(fila=1:5,var1, var2, var3, var4) datos datos fila var1 var2 var3 var4 1 1 0 1 1 1 2 2 0

I would like to know how to turn a variable into a string. I have tried as.symbol and as.name but it doesnt work for what I'd like to do Essentially, I'd like to feed the function below with two variables. This works fine in the bit working out number of elements in each variable. In the print(sprintf("OK with %s and %s\n", var1, var2)) line I would like var1 and var2 to be

I have a data frame whose first colum contains the names of the variables and whose second colum contains the values to assign to them: : kkk <- data.frame(vars=c("var1", "var2", "var3"), vals=c(10, 20, 30), stringsAsFactors=F) If I do : assign(kkk$vars[1], kkk$vals[1]) it works : var1 [1] 10 However, if I try with mapply

Hi guys, I have two data frames: one referred to 2008 and one to 2009. Their structure is identical except for the different data in them. I need to create a vector alfa of the same length of the dataframe 2009 and fill each element with the mean of 2008$var1 conditional to the subgroup indicated by a factor variable in 2009$var2. In this case it would be easy to use the function

Estimados Estoy entrenando hacer funciones que respondan a comandos, en esta caso en la salida gráfica se observa que dice : Exposure=var3 y outcome=var 1 quisiéramos que se reflejan los nombres de la base de datos : var1=estado, var2=cake, var3=chocolate Espero haberme explicado adecuadamente Adjunto tabla con datos #################################### #Comando que llama

Can someone please give me a clue how to 're'write this so I dont need to use loops. a<-ts(matrix(c(1,1,1,10,10,10,20,20,20),nrow=3),names=c('var1','var2','var3')) b<-ts(matrix(c(2,2,2,11,11,11,21,21,21),nrow=3),names=c('var1','var2','var3'))