similar to: model simulation

Hi, I have used DeSolve package for my ODE problem regarding infectious disease transmission and currently am trying to pass lots (roughly a thousand) of model parameters to the C compiled model (I have to use C compiled code instead of R code purely because of the speed). I can't go define it one by one as it gonna take ages to finish and also quite difficult to revise. I have read the

Dear useRs, I want to plot the following barplot with lines instead of bars. Is there a way? data <- data.frame(cbind(k = 0:3, fk = c(11, 20,7,2), f0k = c(13.72, 17.64, 7.56, 1.08), fkest = c(11.85, 17.78, 8.89, 1.48))) d <- t(data[,2:4]) barplot(d, beside=TRUE) Regards, Rafael. ____________________________________________________________________________________ [[elided Yahoo

Hello everyone, I am trying to solve 2D differential equations using finite difference scheme in R. I have been able to work with the equations with only one spatial dimensions but I want to extend it to the two dimensional problem. For example i can simulate one dimensional diffusion using a code like the following. But I want to write a similar code for,say, a two dimensional diffusion

Dear useRs, How can I draw a barplot, but instead of bars, I'd get lines? Thanks, Kind regards, Rafael. ____________________________________________________________________________________ [[elided Yahoo spam]] [[alternative HTML version deleted]]

Dear useRs, I can't seem to find out how to categorize my histogram. I have the following dataset: Time??????????? First.day? Second.day 08:00-10:00??????? 9?????????? ? 8 10:00-12:00?????? 13???????? ? 15 12:00-14:00??????? 9?????????? ? 9 14:00-16:00???????10????????? ? 9 I attached a jpeg file to this e-mail containing the sketches. What I'd like to do is a barplot (or histogram),

Hello all, I'm trying to create a 2x2 matrix, 32 times after unlist() so that I can convert the list to matrix. I've looked through the R archive but couldn't find the answer. There is what I've done. > f <- system("ls *.txt", intern=TRUE) > x <- lapply(f, read.table) > x [[1]] V1 V2 1 -27.3 14.4 2 29.0 -38.1 [[2]] V1 V2 1 14.4

Hello, can anyone tell me if R has any special function for simulating the structure of human populations? Something like the genetic algorithm? I need to simulate a sample of a population with a specific structure. Is there something on R that can help me? Thanks to everyone. __________________________________________________________

Dear useRs, I want to write a function that generates all the possible combinations of diff(). Example: If my vector has length 5, I need the diff() until lag=4 -> c(diff(my.vec), diff(my.vec, lag=2), diff(my.vec, lag=3), diff(my.vec, lag=4)) If it has length 4, I need until lag=3 -> c(diff(my.vec), diff(my.vec, lag=2), diff(my.vec, lag=3)) So, it must be until lag=(length(my.vec)-1).

All- I am interested in estimating a parameter that is the starting value for an ODE model. That is, in the typical combined fitting procedure using nls and lsoda (alternatively rk4), I first defined the ODE model: minmod <- function(t, y, parms) { G <- y[1] X <- y[2] with(as.list(parms),{ I_t <- approx(time, I.input, t)$y dG <- -1*(p1 + X)*G +p1*G_b dX <-

I am experimenting with exporting pointers to some of the functions in deSolve so that other packages may import them, using the 'R_RegisterCCallable' mechanism. I have added a header file and some other C code in inst/include of the deSolve source package that need to be accessible to other packages. I have a site-library set up in Rprofile.site where all installed packages go, and as

HI all, I might add some more information in order to possibly solve my problem. I'm really stuck and no obvious solutions do the trick. I'm using R 1.7.1 on Windows 2000 with the packages regurarly updated. I'm using hypothetical data constructed as a pseudo population conforming to a certain Var-Cov structure. I might add that just > predict(level2) works. But when I add the

Dear useRs, I'm trying to write a loop to sum my data in the following way: (the second - the first) + (the third - the second) + (the fourth - the third) + ... for each column. So, I wrote something like this:   c <- list()   for(i in 1:ncol(mydata)) {   for(j in 2:nrow(mydata)) {   c[[i]] <- sum(yc[j,i] - yc[(j-1),i])   }}} As for the columns it works pretty fine, but it only

Dear list The deSolve package allows you to specify the model code in C or Fortran. Thanks to the excellent vignette this works fine. However I have not yet managed to use forcing functions in C code. In pure R code this works very well with approxfun() specified outside the model: ############################################### #Model lvml <- function(t, x, parms) {

I have a problem integrating the 'standard map' ( http://en.wikipedia.org/wiki/Standard_map http://en.wikipedia.org/wiki/Standard_map ) with deSolve: By using the modulo-operator '%%' with 2*pi in the ODEs (standardmap1), the resulting values of P and Theta, should not be greater than 2pi. Because this was not the case, i was thinking that the function 'ode' has some

Hi All, I am running R 2.2.0 on Mac OS 10.4.2, dual G5 processors with 8 Gig RAM. I am running a simulation with lsoda that requires ~378 s to complete one set of time intervals. I need to optimize the parameters, and so need to considerably speed up the simulation. I have tried to figure out how to change the appropriate memory allocation and have search R help and Introductory

Hi, I've got Gluster error: Transport endpoint not connected. It came up twice after trying to rsync 2 TB filesystem over; it reached about 1.8 TB and got the error. Logs on the server side (on reverse time order): [2012-12-15 00:53:24.747934] I [server-helpers.c:629:server_connection_destroy] 0-RedhawkShared-server: destroyed connection of

I need to solve a system of non-linear fourth-order differential equations. Is there a command which solves this system? Thanks in advance.

My apologies in advance for my thickness but I can't seem to solve the following, seemingly simple, data manipulation problem: I have a data frame that contains multiple factors and multiple continuous response variables, but duplicates of some factor combinations. The duplicates contain bad data, so I would like to eliminate the duplicates. I would like to retain the entire rows

Hi Folks, How do I get red bold font on my y axis and black standard font on my x axis? plot(runif(10), ylab="Red, Bold?", xlab="Black, standard?") Any pointers or examples would be great. Thanks! Hank Dr. Hank Stevens, Assistant Professor 338 Pearson Hall Botany Department Miami University Oxford, OH 45056 Office: (513) 529-4206 Lab: (513) 529-4262 FAX: (513) 529-4243

Hello, I am solving a set of ODEs using deSolve and have run into a problem I would appreciate some advice on. One of the parameters (m) in the ODEs changes between two states when one of the variables (D) crosses a threshold (D_T) for the first time in either direction. Additionally, when the variable crosses the threshold (either by increasing or decreasing), there is a time delay (delay)