similar to: Solving ODEs

I have written a function that uses LSODA from NETLIB to solve initial value problems, given a system of ODEs written as an R function. There are times when it would be convenient to use the code with an ode system written in a compiled language. Certainly, that can be done using .C or .Fortran within an R function, but that seems inefficient (indeed, it does not enormously speed up the

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, Does somebody knows of the existence of a library of functions for solving differential equations, I need a solver for a system of non linear first order differential equations. I think there was something in IMSL but that was a long time ago and probably there are some new algorithms in the new now. Thanks for any pointers. . R. Heberto Ghezzo Ph.D. Meakins-Christie Labs McGill

Hi, I have a data-matrix: > PID sato hrs fim health 214 3 4.376430 6.582958 5 193 6 4.361825 3.138525 6 8441 6 4.205771 3.835886 7 7525 6 4.284489 3.245139 6 6806 7 4.168926 2.821833 7 5682 7 1.788707 1.212653 7 5225 6 1.651463 1.436980 7 4845 6 1.692710 1.267359 4 4552 5 1.686448 1.220539 6

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

Dear all, thank you for your hints. I would prefer to do not use Rserve as Dirk mentioned. @Simon I have full control over the Java implementation - I can adapt the code that I use for the communication R <-> Java. > You can natively access structures on each side. The fastest way is to > use R representation (column-oriented) in Java - that is much faster > than any kind of

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

Dear all, in our ongoing project we use Java implementations of several algorithms. We also provide a ?wrapper? implemented as an R package using rJava (https://github.com/jaroslav-kuchar/rCBA). Based on our recent experiments, the significant portion of time is spent on copying a dataframe from R to Java. The Java implementation needs access to the source dataframe. I have tested several

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)),{

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, 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

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,

Hello, I am developing an agent-based model to simulate the spread of infectious diseases in heterogeneous landscapes composed of habitat polygons (or clumps of connected cells). To simplify the model, I consider a habitat grid (or raster) containing the polygon ID of each cell. In addition, I have epidemiological parameters associated with each polygon ID. At each time step, the parameter values

Hi, I would like to solve a system of coupled ordinary differential equations, where there is a delay (time lag) term. I would like to use the "lsoda" function "odesolve" package. However, I am not sure how to specify the delay term using the syntax allowed by odesolve. Here is an example of the kind of problem that I am trying to solve: > library(odesolve)

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)

Dear R-users, I'm running an MLE procedure where some ODEs are solved for each iteration in the maximization process. I use mle2 for the Maximum likelihood and deSolve for the ODEs. The problem is that somewhere along the way the ODE solver crashes and I get the following error message: DLSODA- Warning..Internal T (=R1) and H (=R2) are such that in the machine, T + H = T on the next

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