similar to: ODE

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 have a syntactic problem with ode. How do I specify vectors of equations in ordinary differential equation systems. (i.e. in my case I want to simulate an a priory undefined number of species that have different parameters but the same behaviour) I demonstrate this using the Lotka Volterra example. The code below does not work and I have not a good idea how to specify this right. ##

Hi, I am trying to run a 1D nutrient-phytoplankton-zooplankton model in R using the package 'deSolve'. The code is shown below: DEPTH = seq(2.5, 147.5, 5) NPZ = function(t, state, params){ with(as.list(params), { P <- state[1:NB] Z <- state[(NB + 1): (2*NB)] N <- state[(2*NB + 1): (3*NB)] F.I = function(z, hr){ I0 = function(hr){

This is applicable to either using optim or the differential equation solver or any similar solver Suppose I want to use the differential equation solver and this is my code d<-y[2] vdpol<-function(t,y) { list(c(1, d, 3, 4 ) } stiff<-ode(y=rep(0,4),times=c(0,1),func=dvdpol,parms=1) The thing is I want d to be composed of one of state variables in the

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 =

I'm getting this error on the attached code and breaking my head but can't figure it out. Any help is much appreciated. Thanks, Vince CODE: library(deSolve) Res_DAE=function(t, y, dy, pars) { with(as.list(c(y, dy, pars)), { res1 = -dS -dES-k2*ES res2 = -dP + k2*ES eq1 = Eo-E -ES eq2 = So-S -ES -P return(list(c(res1, res2, eq1, eq2))) }) } pars <- c(Eo=0.02,

Vince, When that happens, one possible reason is that your DAE is of index > 1, which cannot be solved by daspk. The solver radau, also from deSolve can handle DAEs up to index 3, but you need to rewrite the problem in the form M*y' = f(x,y), where M is a mass matrix. If you do that for your problem, and solve it with radau, then radau complains that the "matrix is repeatedly

Dear R-users, I am currently modifying a previously developed predator prey model and was curious if there was a way to add in a disturbance to the model (let's say at time t=100). The disturbance can be the introduction of 40 prey (N=40) and 10 predators (Pred = 10). I would like to see my model go from a state of equilibrium (up to t = 99), show this disturbance (at t = 100) and then

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 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 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 ?

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

Hi, I did some googling. I found multiple ODE solver packages. But I am wondering if there is any terminal value ODE solver (linear case) for multi-dimension case or not? I have not come across any. Any guidance would be appreciated. Robert [[alternative HTML version deleted]]

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 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

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'm used to working with R in estimation of distributions and statistical models. I'd like to estimate a simple model of an output y(t) based on a concentration as independent variable, using a timed series of experimental data; I've seen this I think somewhere in R? I'd appreciate to hear if anybody has used this with success. regards, S

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