similar to: Optimize parameters of ODE Problem which is solved numeric

I have tried multiple different methods to figure out how to get a date axis of my preference (start date of each month). Any assistance would be appreciated. The below section is not producing a date axis: plot(totaldays$totaldays,totaldays$y,type="n",ylim=c(0,Emax),xaxt="n") *xlabels<-(strptime(totaldays$totaldays,"%Y-%m-%d",tz=""))

Hello, I'm pretty new to R. Basically, how do I speed up the for loop below. Or better yet, get rid of the for loop all together. objective: plot two data sets column against column by index. These data sets have alot NA's. Some columns are all NA's. I need the plots to overlay. I don't like the plots in matplot(). Needs to be much faster than the code below... #simple sample

Hi there R-helpers: I'm having problems with the function ode() found in the package deSolve. It seems that when my state variables are too numerous (>33000 elements), the function throws the following error: Error in vode(y, times, func, parms, ...) : cannot allocate memory block of size 137438953456.0 Gb In addition: Warning message: In vode(y, times, func, parms, ...) : NAs

Hi all, I try to assess the parameters (K1,K2) of a model that describes the adsorption of a molecule onto on adsorbent. equation: dq/dt = K1*C*(qm-q)-K2*q I know the value of 'qm' and I experimentally measure the variables 'q', 'C', and the time 't'. t C q 1 0 144.05047 0.0000000 2 565 99.71492 0.1105625 3 988 74.99426

I'm just getting to grips with using ode function and have used the examples and vignettes to produce a small model of a one-pool, michaelis-menten, enzyme kinetic reaction. The rate of flux of substrate into pool A is constant (fluxoa) however the rate of flux out of pool A is controlled by the HMM equation (v = Vmax/ ( 1 + (Km / Concentration A )) ). This function works fine and

Hello All, I'm struggling to solve this ODE using R, vdpol <- function (h, v, t) ( list(c ( -0.1*v/(pi*(2*10*h-h^2)), (v = (-0.1*v/(pi*(2*10*h-h^2))^2) + 2*9.81*h)) )) library(deSolve) yini <- (c(h = 20, v=0)) nonstiff <- ode(y = yini, func = vdpol, times= seq(0, 30, by =

Dear All, I was using rk4 and lsoda to solve a ODE system. However, both of them gave bad accurate solutions, especially compared with Matlab solver ODE45. For example, ODE45 gave solutions that can go to a stable level (about 1.6) when time goes to infinity, however, the solutions from lsoda are decreasing to very very small (about 1e-130) numbers. Does R have more accurate ODE solvers as

I am trying to to write a wrapper function for the ode solver (under the package desolve) to enable it to take multivariate arrays. I know how to do it for 1 dimension arrays but my code breaks down when I try to do it for 2 dimensional arrays. Here is my code diffwrap<-function(t,y,mu)vdpol(t=t,A[1:3,1:4]<-y[1:12],B[1:12]<-y[13:24],mu=mu) vdpol<-function(t,A,B,mu) { list(c(mu,

I tried to use lsode with precompiled C code instead of an R function defining the derivatives. No problem so far. However, now I need to implement an ODE that contains spline functions, i.e. the derivatives at given time points depend on the value of a spline function at this time point. What is an efficient way to implement this in precompiled C code? -- Daniel Kaschek <daniel.kaschek at

I am trying to use the package ode and periodically it will come up with this error message Warning..Internal T (=R1) and H (=R2) are such that in the machine, T + H = T on the next step (H = step size). Solver will continue anyway. And then the program just take very long to run. Is there anyway to get the program to terminate when this warning is issued instead of continuing to run ?

Hello, I am trying to get the output from the numerical simulation of a system of ordinary differential equations for a range of values for three parameters. I am using the ode() function (deSolve package) to run the numerical simulation and apply() to run the simulation function for each set of parameter values. I am having trouble getting the apply() function to work. Here is an

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

Dear R users, I have a problem with reshaping data. I know such questions have been asked before, but I can't get it right, neither with the reshape function nor with the melt function. My dataset has about 407 variables and about 48000 cases. Each case looks as follows: V1 v2 v3 v4 v5 v6 v7 x1 y1 x2 y2 .... x200 y200 V1 is unique, v2-v7 are

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) {

Hello. Does Samba or the CIFS protocol support files replication/migration? Regards Brain -------------------------------- Petr `Brain' Kulhavy <brain@artax.karlin.mff.cuni.cz> http://artax.karlin.mff.cuni.cz/~brain Faculty of Mathematics and Physics, Charles University Prague, Czech Republic --- A man without a woman is like a statue without pigeons.

Hi Listers, This has a simple answer but it has been eluding me nonetheless. I have been building a PCA plot from scratch with the ability to plot predefined groups in different colors. This has worked fine but when I try to get a polygon drawn around each of the groups it is not recognising my colour file correctly and is only printing the first colour in the file....code is below

library(dplyr) DM <- read.table( text='GR x y A 25 125 A 23 135 . . . ) DM %>% filter((GR == "A" & (x >= 15) & (x <= 30)) | (GR == "B" & (x >= 40) & (x <= 50)) | (GR == "C" & (x >= 60) & (x <= 75))) On Fri, Dec 8, 2017 at 4:48 PM, Ashta <sewashm at gmail.com>

Hi all, I study epidemiology of soilborne disease. I have this ode model dS/dt = - (rp(t) X + rs(t) I) * S with X=1 ; rp(t) = ap exp( - bp*t) ; rs(t) = as exp (-0.5 ( ln (t/ds) / bs)? ) The data I have are not directly the infected individuals (which is a hidden state) but the Diseases ones (individuals who show aerial symptoms). I have studied with experiments the relationship between the

Dear Colleague: I am glad to hear from you. I was going to contact you and ask if you have notes on the steps involved on how you implemented LSODA. I will gladly take the project on. In addition to dassl, I want to implement ODESSA also. In other words, my project is a "suite" of ode solvers for R. The application of these solvers will be to the study of the distribution of

Dear all, I am having trouble with the following problem. Suppose we have the fourth order ODE with boundary conditions: http://r.789695.n4.nabble.com/file/n4591748/problem.jpg problem.jpg where q(t) is a known function. Note here the lambda parameter is changing, so essentially we have a series of ODEs. lambda is called an eigenvalue, the solution y is called an eigenfunction associated with