similar to: Fitting compartmental model with nls and lsoda?

R help list subscribers, I am a new user of R. I am attempting to use R to explore a set of equations specifying the dynamics of a three trophic level food chain. I have put together this code for the function that is to be evaluted by LSODA. My equations Rprime, Cprime, and Pprime are meant to describe the actual equation of the derivative. When I run LSODA, I do not get the output that

I'm solving the differential equation dy/dx = xy-1 with y(0) = sqrt(pi/2). This can be used in computing the tail of the normal distribution. (The actual solution is y(x) = exp(x^2/2) * Integral_x_inf {exp(-t^2/2) dt} = Integral_0_inf {exp (-xt - t^2/2) dt}. For large x, y ~ 1/x, starting around x~2.) I'm testing both lsoda and rk4 from the package odesolve. rk4 is accurate using step

I'm trying to use odesolve for integrating various series of coupled 1st order differential equations (derived from a system of enzymatic catalysis and copied below, apologies for the excessively long set of parameters). The thing that confuses me is that, whilst I can run the function rk4: out <- rk4(y=y,times=times,func=func, parms=parms) and the results look not unreasonable:

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 <-

Dear List, Wonder if you have some thoughts on the following question using lsoda in desolve: I have the following data and function: require(deSolve) times <- c(0:24) tin  <- 0.5 D <- 400 V    <- 26.3 k <-0.056 k12  <- 0.197118 k21  <- 0.022665 yini <- c(dy1 = 0,dy2 = 0)  events <- data.frame(var = "dy1",time = c(10,15),value = c(200,100),method =

Dear Michael, One key is adjustment of nls optimizer tolerance. I notice it has to be higher than usual, but, I recovered your noisy "known" parameter values with an error of K1 (-7%) and k1 (-6%): #### Miller problem with Dalgaard modifications ## Linares 1/22/2004 ## Solution 1 nls(noisy ~ lsoda(xstart, time, one.compartment.model, c(K1=K1, k2=k2))[,2], data=C1.lsoda,

Hi - I am getting different results when I run the numerical integrator function lsoda (odesolve package) on a Mac and a PC. I am trying to simulating a system of 10 ODE's with two exogenous pulsed inputs to the system, and have had reasonably good success with many model parameter sets. Under some parameter sets, however, the simulations fail on the Mac (see error message below). The

Hello! I would like to know if R can solve Differential Equations... I don't think so because, in my point, I see R like a Statistical System, not a Math System. Am I wrong? Thank you very much. M??rcio de Medeiros Ribeiro Graduando em Ci??ncia da Computa????o Departamento de Tecnologia da Informa????o - TCI Universidade Federal de Alagoas - UFAL Macei?? - Alagoas - Brasil Projeto CoCADa

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

Hi, I'm new to R and have a problem with a little test program (see below). Why doesn't <<- in function rk4 assign the new value to y so that it is seen in rktest. I thought that <<- does exactly this. But it seems that I didn't get it right. I would be very appreciative for an explanation of that behaviour of <<-. I know how to write the whole thing so that it

Hi, I am doing a project on the simulation of glucose metabolism based on a pharmacokinetic modeling in which we have 4 differential equations. I did this in R by using the odesolve package. It works very well, but I have two questions: Here is the odemodel function _________________________________________________ Ogtt.Odemodel <- function(t, y, p) { absx <- c(-60, -45, -30,

Hello, I want to know if there are some functions or packages to solve differential and integral equation using R. Thanks. Shao chunxuan. [[alternative HTML version deleted]]

Dear All, I have a pair of .cpp and .def file can be compiled using VC++ and works perfectly well in S-PLUS. I wanted to do the same for R; so I followed the guidline given in "Building from a source-code library under Windows" as much as possible and manage to compile them using VC++ and call it from R. But it gives different answer from the one called from S-Plus. I know that I did

I am running R 1.2.3 with ESS5.1.18 with Windows 98. I am trying to use lsoda in the odesolve apckage and am having problems. Question: The return value of the function of the system of ode's has to be a list that includes first, the ode's and second, "a vector (possibly with a `names' attribute) of global values that are required at each point in `times'." I

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) {

Dear list - Does anyone have any ideas / comments about why I am receiving the following warning when I run lsoda: 1: lsoda-- at t (=r1), too much accuracy requested in: lsoda(start, times, model, parms) 2: for precision of machine.. see tolsf (=r2) in: lsoda(start, times, model, parms) I have tried changing both rtol and atol but without success. I saw the thread in the

Installing odesolve in Raqua 1.8.0 or 1.8.1 under MacOSX gives the following message: Warning message: Installation of package odesolve had non-zero exit status in: install.packages(ui.pkgs, CRAN = getOption(where), lib = .libPaths()[1]) Moreover, in the source of odesolve is no makefile. Does anyone know how to get a proper installation? Maartje

Dear All, I am trying to use ode solver "rk4" to solve an ODE system, however, it keeps saying: Error in eval(expr, envir, enclos) : object "dIN" not found. The sample codes are enclosed as follows, please help me. Thank you very much! rm(list=ls()) library(odesolve) # The ODE system ode <- function(t,x,p){ with(as.list(c(x,p)),{

Dear All, I am trying to use ode solver "rk4" to solve an ODE system, however, it keeps saying: Error in eval(expr, envir, enclos) : object "dIN" not found. The sample codes are enclosed as follows, please help me. Thank you very much! rm(list=ls()) library(odesolve) # The ODE system ode <- function(t,x,p){ with(as.list(c(x,p)),{

Hello, I am an R newbie, trying to use lsoda to solve standard Lotka-Volterra competition equations. My question is: how do I pass a parameter that varies with time, like say, phix <- 0.7 + runif(tmax) in the example below. # defining function lotvol <- function(t,n,p){ x <- n[1]; y <- n[2] rx <- p["rx"]; ry <- p["ry"] Kx <-