similar to: Randomly generating data

Dear R-help, I am trying to write a function to simulate datasets of size n which contain two time-to-event outcome variables with associated 'Event'/'Censored' indicator variables (flag1 and flag2 respectively). One of these indicator variables needs to be dependent on the other, so I am creating the first and trying to use this to create the second using an if/else statement.

Dear R-helpers, I would like to generate a variable that takes 0 or 1, and each subject has different probabilities of taking the draw. So, which of the following code I should use ? suppose there are 5 subjects, and their probabilities of this Bernoulli variable is p=c(0.2, 0.9, 0.15, 0.8, 0.75) n<-5 Ber.var <- rbimon(n,1,p) ## I doubt if this will take the first probability, which is

Dear all I want to simulate a stochastic jump variance process where N is Bernoulli with intensity lambda0 + lambda1*Vt. lambda0 is constant and lambda1 can be interpreted as a regression coefficient on the current variance level Vt. J is a scaling factor How can I rewrite this avoiding the loop structure which is very time-consuming for long simulations? for (i in 1:N){ ... N <- rbinom(n=1,

Dear list, I did simulations in which I generated 10000 independent Bernoulli(0.5)-sequences of length 100. I estimated p for each sequence and I also estimated the conditional probability that a one is followed by another one (which should be p as well). However, the second probability is significantly smaller than 0.5 (namely about 0.494, see below) and of course smaller than the direct

Dear all, I just want to determine if the characters in a character string are the same or not. For example, temp <- c("aa", "aA", "ab") How do I determine the first one have the two same ?a?, and the second and third have the different characters? Thanks in advance. Lisa -- View this message in context:

Hi all, I was wondering how to generate samples for two RVs X1 and X2. X1 ~ Bernoulli (p1) X2 ~ Bernoulli (p2) Also, X1 and X2 are correlated with correlation \rho. Regards, Vineet [[alternative HTML version deleted]]

Dear all, I have a dataset that looks like this: x <- read.table(textConnection("col1 col2 3 1 2 2 4 7 8 6 5 10"), header=TRUE) I want to rewrite it as below: var1 var2 var3 var4 var5 var6 var7 var8 var9 var10 1 0 1 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0

Dear all, I am trying to write a script to pause the execution of a function and provide some additional commands to the function and then continue execution of the function. For example, when my function detects a wrong number in a dataset, the function pauses automatically and returns information on the screen: ?There is a wrong number in the dataset. Would you like to correct it? ? If I

Can someone explain why I am getting the following error: in the r code below? Error in solve.default(diag(2) + ((1/currvar) * (XX1 %*% t(XX1)))) : system is computationally singular: reciprocal condition number = 0 In addition: There were 50 or more warnings (use warnings() to see the first 50) The R code is part of a bigger program. ##sample from full conditional

Dear all, I have a question about how to set arguments in my own function. For example, I have a function that looks like this: my.f <- function(a = x1, b = x2) { x1 = equation 1 x2 = equation 2 x3 = equation 3 y = a + b } x1, x2, and x3 are temporary variables (intermediate results) calculated from other variables within the funciton. I want to use two of these three

Hello, All, I have a dataset that looks like this: x <- matrix(c( 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 2, 1, 1, 2, 1, 1, 3, 1, 1, 3, 1, 1, 3, 1), ncol = 5, byrow = T, dimnames = list(1:10, c("gender", "race", "disease"))) I want to write a function to produce several matrices including only ?TRUE? and ?FALSE? for the different levels of the

HI, Dear Greg, I AM A NEW to GBM package. Can boosting decision tree be implemented in 'gbm' package? Or 'gbm' can only be used for regression? IF can, DO I need to combine the rpart and gbm command? Thanks so much! -- Sincerely, Changbin -- [[alternative HTML version deleted]]

Dear R-listers, Can someone suggest a method for generating a finite Bernoulli sequence that is likely to have a given point-biserial correlation with an existing Bernoulli sequence? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall

Dear all, I have a question about deleting components of a list. For example, I have a list that looks like this: [[1]] var1 var2 var3 1 3 4 2 2 1 [[2]] var1 var2 var3 2 5 1 2 1 7 [[3]] var1 var2 var3 1 6 7 3 8 4 How to delete, say, the first columns of the list or the second rows? Thank in advance. Lisa -- View

Dear all, I have two sets of numbers that look like a <- c(1, 2, 3, 3, 4, 4, 5, 6, 1, 2, 2, 3, 1, 2, 1, 2, 3, 3, 4, 5, 1, 2, 3, 4) b <- c(1, 5, 8, 9, 14, 20, 3, 10, 12, 6, 16, 7, 11, 13, 17, 18, 2, 4, 15, 19) I just want to use ?b? to encode ?a? so that ?a? looks like a1<- c(1, 5, 8, 8, 9, 9, 14, 20, 3, 10, 10, 12, 6, 16, 7, 11, 13, 13, 17, 18, 2, 4, 15, 19) Does anyone have a

Dear all, I have a dataset that looks like this: inividual var1 var2 ? 1 1 1 ? 2 1 2 ? 3 2 1 ? 4 2 2 ? ? ? ? ? I will random sample 2 individuals from this dataset based on a set of random numbers, e.g., rn1 <- c(0, 0, 1, 1), rn2 <- c(0, 0, 2, 0), rn3 <- c(1, 0, 0, 1), rn4 <-

Dear all, I have a question about how to suppress intermediate results in a function on console. For example, I will use summary() in my own function that looks like: myfunction <- function(?) { ? Summary(x) ? } Then myfunction() will print ?x? on console that is intermediate result and doesn?t need showing. Does someone have any idea or any suggestion? Thank you in advance. Lisa

Hello, All, I want to write a function to do some works based on the arguments. For example, bind some variables (arguments) as this: myfunction <- function(arg1, arg2, arg3, ?) { x <- cbind(arg1, arg2, arg3, ?) } myfunction(arg1, arg2, arg3, ?) The function can automatically determine the number of arguments and bind them, which means if I assign 2 arguments, the function can bind

Hi, everybody, I just want to pass arguments to a function as below: range <- c(0.1, 0.5) runif(1, range) But it doesn?t work. Does anyone have any suggestions to offer? Thanks. Lisa -- View this message in context: http://r.789695.n4.nabble.com/Arguments-of-a-function-tp3387643p3387643.html Sent from the R help mailing list archive at Nabble.com.

Dear R-users, I'm running a lmer model using the lme4 package. My dependent variable is dichotomous and I'm using the "binomial" family. The results are slightly different from the HLM results based on a Bernoulli distribution. I read that a Bernoulli distribution is an extension of a binomial distribution. Is that right? If so, how can I adapt my R model to a Bernoulli