similar to: search for variable in package in .GlobalEnv first

Hi I have a table called npl containing results of simulations. It contains about 19000 entries and the structure looks like this: NoPlants sim run year DensPlants 1 6 lng_cs99_renosterbos 1 4 0.00192 . . . it has 43 different entries for sim and year goes from 1 to 100, and run from 1 to 5. I would like to calculate the mean of DensPlants for each

Hi I generate a new dataframe by doing: npl.agg <- aggregate(npl$DensPlants, list(year=npl$year, sim=npl$sim), mean, na.rm=TRUE ) Now I want to plot it by using coplot(npl.agg$x ~ npl.agg$year | npl.agg$sim, type="l") but, as npl.agg$year is seen as a factor, the order of the points on the x-axis (time axis) does not follow the numerical sorting 1...100, but rather the text

Hi, I am trying to figure out the observed acceptance rate and M, using generalised rejection sampling to generate a sample from the posterior distribution for p. I have been told my code doesn't work because I need to "take the log of the expression for M, evaluate it and then exponentiate the result." This is because R is unable to calculate high powers such as 545.501. As

Dear all, I've been having problems running update() to re-fit a cpglm model inside a function (as in the code below). The solution is probably simple, but I'm stuck. If anyone could help, I'd greatly appreciate it. Regards, Rubem ## R code library(cplm) ## Data simulation period<-factor(1:4)                        herd<-factor(1:50)  

Hi, I'm trying the brlr function in a penalized logistic regression function. However, I am not sure why I am encountering errors. I hope to seek your advice here. (output below) Thank you! Your help is truly appreciated. Min-Han #No error here, the glm seems to work fine >

Dear guRus, I am trying to replace "~" by "$\sim$" for TeX. However, I can't get the backslash to work. I would like to turn "DV~IV" into "DV$\sim$IV". sub("~","$\sim$","DV~IV") => "DV$sim$IV" sub("~","$\\sim$","DV~IV") => "DV$sim$IV"

Hi, I have a large data frame and within this there is one column which contains individual codes (eg. 1.1234.2a.2). I am splitting these codes into their 4 components using strsplit (eg. "1", "1234", "2a", "2"). However there are some individual codes which do not have a last component (eg. 2.4356.3b. ), I want to give these codes a "1" as their

Hi, I'm using RF to simulate a correlated variable with GaussRF set.seed=1 GaussRF(sim.kfinegrid, grid=F, model="exponential", param=c(0,0.5,0,0.2)) However when I simulate again using the same random seed I get different results. > set.seed=1 > summary(GaussRF(sim.kfinegrid, grid=F, model="exponential", param=c(0,0.5,0,0.2))) Min. 1st Qu. Median Mean 3rd

Dear List, I am relatively new to R and am trying to create more attractive plots than excel can manage! I have looked through the various programmes ggplot, lattice, hmisc etc but my case seems to be not metnioned, maybe it is but i have not noticed - if this is the case i apologise.

Hi, i have a strange situation: A domain is still running where domblklist points to a snapshot file and also dumpxml says the current drive is that snapshot file. But the file has been deleted hours ago. And the domain is still running. I can login via ssh, the database and the webserver are still running, domain is performant. How can that be ? Also lsof shows that the file is deleted:

Hi all Is there any reason why the parameter i in a "for" loop ignores a value of zero? For example sim=c() p=.2 for(i in 0:5) {sim[i]=dbinom(i,5,p) } sim [1] 0.40960 0.20480 0.05120 0.00640 0.00032 In this example the quantile i= 0 was ignored since dbinom(0,5,p) [1] 0.32768 The same behaviour occurs if I use a while loop to perform the same calculation: sim=c() p=.2 i=0

Dear all, I have a data frame with one factor and four numeric variables and wish to obtain the var-cor matrix separately by factor. I tried by() and sapply() but getting nowhere. I understand this can be done by subsetting the dataframe, but there should have some sleek ways of doing it. Here is a simulated dataframe; s <- rep(c("A","B","C"), c(25,22,18)) d

Dear r-helpers, Spencer Graves and Manual Morales proposed the following methods to simulate p-values in lme4: ************preliminary************ require(lme4) require(MASS) summary(glm(y ~ lbase*trt + lage + V4, family = poisson, data = epil), cor = FALSE) epil2 <- epil[epil$period == 1, ] epil2["period"] <- rep(0, 59); epil2["y"] <- epil2["base"]

Dear R-users, I would like to show you a simple example that gives an overview of one of my current issue. Although my working setting implies a different parametric model (which cannot be framed in the glm), I guess that what I'll get from the following example it would help for the next steps. Anyway here it is. Firstly I simulated from a series of exposures, a series of deaths (given a

Hi, Can anyone help sort out the problem with the following script - I am a R newbie and I am self taught. obs.all = c() for(i in 1:386){ if (n.sim[i]>0){ obs = (1:133429)[event.details[,2] == i] obs.all = c(obs.all, sample(obs[obs < n.sim[i]], size = n.sim[i], replace=T)) } Basically, in the sample bit, I only want to get obs.all if the value of

In some time series simulations I'm doing, I occasionally want the model to be ``white noise'', i.e. no model at all. I thought it would be nice if I could fit this into the arima.sim() context, without making an exceptional case. I.e. one ***could*** do something to the effect if(length(model)==0) x <- rnorm(n) else x <- arima.sim(model,n) but it would be more suave if one

Hi R users, Does anyone know how to change the size of 3d charts? I'm using surface3d in rgl package, opening a new window each time to display the chart. I want it so that the chart fills the whole window, because when I output it to png, I don't want all the white space around the chart (right now, i'm getting this white "border" around the chart because the chart is

Hello all. I am trying to run PAN, multilevel multiple imputation program, in R to impute missing data in a longitudinal dataset. I could successfully run the multiple imputation when I only imputed one variable. However, when I tried to impute a time-varying covariate as well as a response variable, I received an error message, “Error: subscript out of bounds.” Can anyone tell if my commands

Dear all, I have been trying to investigate the behaviour of different weights in weighted regression for a dataset with lots of missing data. As a start I simulated some data using the following: library(MASS) N <- 200 sigma <- matrix(c(1, .5, .5, 1), nrow = 2) sim.set <- as.data.frame(mvrnorm(N, c(0, 0), sigma)) colnames(sim.set) <- c('x1', 'x2') # x1 & x2 are

Hello, I have used the arima.sim function to generate a lot of time series, but to day I got som results that I didn't quite understand. Generating two time series z0 and z1 as eps <- rnorm(n, sd=0.03) z0 <- arima.sim(list(ar=c(0.9)), n=n, innov=eps) and z1 <- arima.sim(list(ar=c(0.9)), n=n, sd=0.03), I would expect z0 and z1 to be qualitatively similar. However, with n=10 the