search for: lsoda

...ial 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 length 10^-2 and probably would be with even larger steps. lsoda is pretty accurate out to about x=4, then starts acting strangely. For step length 10^-3, y suddenly starts to increase after 4, when it should be strictly decreasing. For...

Dear Colleagues, Our group is also working on implementing the use of R for pharmacokinetic compartmental analysis. Perhaps I have missed something, but > fit <- nls(noisy ~ lsoda(xstart, time, one.compartment.model, c(K1=0.5, k2=0.5)), + data=C1.lsoda, + start=list(K1=0.3, k2=0.7), + trace=T + ) Error in eval(as.name(varName), data) : Object "C1.lsoda" not found What part of the e-mail did I miss? I would like to get th...

...hael, 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, start=list(K1=0.3, k2=0.7), control=nls.control(maxiter=50,tol=1), trace=T ) 0.3594355 : 0.3 0.7 0.006118908 : 0.3456684 0.3518834 0.002828044 : 0.4057868 0.40...

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 R-archive of 11 Jun...

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 be...

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 these equations should be giving. Can someone tell me if I have set this function up correctly to use with LSODA when the user is specifying th...

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"];...

...() { ....... for( i in 1:Subject) { kel<-par1 Vd<-par2 PKindex<-sbolus1.out(PKtime,kel,Vd,defun,par1,par2,Dose,i) } savefile(PKindex) } sbolus1.out<-function(PKtime,kel,Vd,defun,par1,par2,Dose,i) { time<-PKtime$time parms<-c(kel=kel,Vd=Vd) C1.lsoda<-data.frame(lsoda(Dose/Vd,c(0,time),defun,parms)) cat("\n") sim<-matrix(c(kel,Vd,par1,par2),2,2) dimnames(sim)<-list(c("kel","Vd"),c("Value","Original")) show(sim) cat("\n\n<< Output >>\n\n") good<-ifelse...

I have been trying to make use of the odesolve library on my university's Linux grid - currently R version 2.0.1 is installed and the system runs 64-bit Scientific Linux based on Redhat. I cannot seem to get lsoda working when I define the model as a shared C library. For example, the following snippet uses the mymod.c example bundled with the package: ### START rm(list=ls()) setwd("~/projects/test_odesolve") invisible(file.remove("mymod.o","mymod.so")) system("R CMD SHL...

...unction rk4: out <- rk4(y=y,times=times,func=func, parms=parms) and the results look not unreasonable: out<-as.data.frame(out) par(mfrow=c(4,1)) for (i in 2:(dim(out)[2]))plot(out[,1],out[,i], pch=".", xlab="time", ylab=names(out)[i]) If I try doing the same thing with lsoda: out <- lsoda(y=y,times=times,func=func, parms=parms, rtol=1e-1, atol= 1e-1) I run into problems with a series of 'Excessive precision requested' warnings with no output beyond the first time point. Fiddling with rtol and atol doesn't seem to do very much. What is likely to be ca...

Hi, I have a system of ODE's I can solve with lsoda. Model=function(t,x,parms) { #parameter definitions lambda=parms[1]; beta=parms[2]; d = parms[3]; delta = parms[4]; p=parms[5]; c=parms[6] xdot[1] = lambda - (d*x[1])- (beta*x[3]*x[1]) xdot[2] = (beta*x[3]*x[1]) - (delta*x[2]) xdot[3] = (p*x[2]) - (c*...

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...

Thanks to Dieter Menne and Spencer Graves I started to get my way through lsoda() Now I need to use it in with nls() to assess parameters I have a go with a basic example dy/dt = K1*conc I try to assess the value of K1 from a simulated data set with a K1 close to 2. Here is (I think) the best code that I've done so far even though it crashes when I call nls() --------...

I'm running an LSODA to generate some graphs, but I need to stop at a certain point and use those values to generate another LSODA output. This is working fine, but when I try to run the second LSODA, I get the "Error in eval(expr, envir, enclos) : object 'N' not found". Any ideas what can be causin...

...y to do, but suppose you have a system of equations like this, dP1/dt = beta1*P1*V1 - mu1*P1 dP2/dt = beta2*P2*V2 - mu2*P2 dV1/dt = r1*V1 - beta1*P1*V1 dV2/dt = r1*V2 - beta1*P2*V2 System 1 and system 2 are independent but that doesn't need to be the case. Now can you specify this system in lsoda() as: dP/dt = beta*P*V - mu*P dV/dt = r*V - beta*P*V but now the initial state variables are 1x2 vectors and the parameters beta, mu and r are also vectors of size 1x2: y=c(10,20,10,20) parms = matrix(c(0.05,0.1,0.2,0.05,0.1,0.2),nc=3,byrow=T) model = function(times,y,parms) { y=matrix(y,nc=2...

...0.0 faster by setting the derivatives even larger in absolute value. You may run into problems with the solver when the derivatives are discontinuous functions of the state variables. There is a simple and elegant solution in theory, but not (yet) available in odesolve. soda has a variant called lsodar that returns whenever a function of the state variables satisfies a given set of conditions (in your case, you could tell lsodar to return whenever any state variable drops below 0.4). Once the call to lsodar returns, you'd then reset all the state variables that were < 0.4 to 0, and resta...

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 information and the archives...

Hello, I wanted to test the odesolve package and tried to use compiled C-code. But when I do: erg <- lsoda(y, times, "mond", parms, rtol, atol, tcrit=NULL, jacfunc=NULL, verbose=FALSE, dllname="mond", hmin=0, hmax=Inf) I get the error message: Error in lsoda(y, times, "mond", parms, rtol, atol, tcrit = NULL, jacfunc = NULL, :...

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),me...

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...