similar to: Printing status updates in while-loop

Dear all, I'm working with a code that consists of two parts: In Part 1 I'm generating a random graph using the igraph library (which represents the relationships between different nodes) and a vector (which represents a certain characteristic for each node): library(igraph) g <- watts.strogatz.game(1,100,5,0.05) z <- rlnorm(100,0,1) In Part 2 I'm iteratively changing the

Dear all, I'm currently running R on my laptop -- a Lenovo Thinkpad X201 (Intel Core i7 CPU, M620, 2.67 Ghz, 8 GB RAM). The problem is that some of my calculations run for several days sometimes even weeks (mainly simulations over a large parameter space). Depending on the external conditions, my laptop sometimes shuts down due to overheating. I'm now thinking about buying a more

Dear all, I'm running a coxph model of the form: coxph(Surv(Start, End, Death.ID) ~ x1 + x2 + a1 + a2 + a3) Within this model, I would like to compare the influence of x1 and x2 on the hazard rate. Specifically I am interested in testing whether the estimated coefficient for x1 is equal (or not) to the estimated coefficient for x2. I was thinking of using a Chow-test for this but the Chow

Dear all, I am trying to simulate a series of networks that have characteristics similar to real life social networks. Specifically I am interested in networks that have (a) a reasonable degree of clustering (as measured by the transitivity function in igraph) and (b) a reasonable degree of degree polarization (as measured by the average degree of the top 10% nodes with highest degree divided by

Dear all, is there a convenient way to determine the effect size for a regression coefficient in a multiple regression model? I have a model of the form lm(y ~ A*B*C*D) and would like to determine Cohen's f2 (http://en.wikipedia.org/wiki/Effect_size) for each predictor without having to do it manually. Thanks, Michael Michael Haenlein Associate Professor of Marketing ESCP Europe Paris,

Dear all, I have a discrete distribution showing how age is distributed across a population using a certain set of bands: Age <- matrix(c(74045062, 71978405, 122718362, 40489415), ncol=1, dimnames=list(c("<18", "18-34", "35-64", "65+"),c())) Age_dist <- Age/sum(Age) For example I know that 23.94% of all people are between 0-18 years, 23.28%

Dear all, I'm struggling with predicting "expected time until death" for a coxph and survreg model. I have two datasets. Dataset 1 includes a certain number of people for which I know a vector of covariates (age, gender, etc.) and their event times (i.e., I know whether they have died and when if death occurred prior to the end of the observation period). Dataset 2 includes another

Dear all, I would like to solve a problem similar to a multiple knapsack problem and am looking for a function in R that can help me. Specifically, my situation is as follows: I have a list of n items which I would like to allocate to m groups with fixed size. Each item has a certain profit value and this profit depends on the type of group the item is in. My problem is to allocate the items

Dear all, I am running a simulation in which I randomly generate a series of vectors to test whether they fulfill a certain condition. In most cases, there is no problem. But from time to time, the (randomly) generated vectors are too large for my system and I get the error message: "Cannot allocate vector of size x". The problem is that in those cases my simulation stops and I have to

Dear all, I'm working with two data frames. The first frame (agg_data) consists of two columns. agg_data[,1] is a unique ID for each row and agg_data[,2] contains a continuous variable. The second data frame (geo_data) consists of several columns. One of these columns (geo_data$ZCTA) corresponds to the unique ID in the first data frame. The problem is that only a subset of the unique ID

Dear all, I have a continuous variable that can take on values between 0 and 100, for example: x<-runif(100,0,100) I also have a second variable that defines a series of thresholds, for example: y<-c(3, 4.5, 6, 8) I would like to convert my continuous variable into a discrete one using the threshold variables: If x is between 0 and 3 the discrete variable should be 1 If x is between 3

Dear all, I would like to run a simple regression model y~x1+x2+x3+... The problem is that I have a lot of independent variables (xi) -- around one hundred -- and that some of them are categorical with a lot of categories (like, for example, ZIP code). One straightforward way would be to (a) transform all categorical variables into 1/0 dummies and (b) enter all the variables into an lm model.

Dear all, This is probably more related to statistics than to [R] but I hope someone can give me an idea how to solve it nevertheless: Assume I have a variable y that is a function of x: y=f(x). I know the average value of y for different intervals of x. For example, I know that in the interval[0;x1] the average y is y1, in the interval [x1;x2] the average y is y2 and so forth. I would like to

Dear list, I'm trying to write my first looping function in R. After many hours of searching help files and previous posts, I'm at wits end. Please forgive my programming ignorance...any help is greatly appreciated. I need to sort through a vector (x) and identify the point at which 2 successive values become smaller than the previous value. I've written a "while"

Dear all, I have a data.frame that includes a series of demographic variables for a set of respondents plus a dependent variable (Theta). For example: Age Education Marital Familysize Income Housing Theta 1: 50 Associate degree Divorced 4 70K+ Owned with mortgage 9.147777 2: 65

Hello, I am trying to assign a variable name (x1,x2,x3...) in a loop statement that is based on a counter (counter is based on the number of hours within the datafile). The x1,x2 data will later be called for plotting the data. Below is a clip of the for loop I am using, any suggestions? k = 1 for (i in 1:length(stats$hour)) { "x(i)" = dataset[k,(3:15)] k = k+1 } Thanks,

Hi to all, seems to be simple, but I do not find the solution: What must I write for the splitted ???? to get splitted$"3"$x and splitted$"3"$x y = c(rep(2,5),rep(3,5)) ma <- data.frame(x = 1:10, y=y ) splitted <- split(ma, ma$y) for (counter in (min(ma$y):max(ma$y))) { splitted????$x } Regards Knut

Just moving a chunk of files from one filesysstem on xvba to another on xvdb, and was monitoring with xentop as it was taking longer than expected. The VBD_RD and VBD_WR counters were both clocking-up as expected, as was the VBD_RSECT counter, but the VBD_WSECT counter was stuck on zero, I toggled on the individual VBD device counters and these showed the same (with the RD and WR counters

Just moving a chunk of files from one filesysstem on xvba to another on xvdb, and was monitoring with xentop as it was taking longer than expected. The VBD_RD and VBD_WR counters were both clocking-up as expected, as was the VBD_RSECT counter, but the VBD_WSECT counter was stuck on zero, I toggled on the individual VBD device counters and these showed the same (with the RD and WR counters

Dear all The following is a very basic and beginner's question on loops. Suppose you have data (say, 1000 cases) with two variables named "answer" (string) and "class" (numeric). The latter runs from 1 to 78 and categorizes the data. I need to create a file "answer_1.txt" for the cases with class==1, and so on, up to "answer_78.txt" I have been