similar to: ODE solver

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

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 *think* this might be better posted here: https://bioconductor.org/help/support/ Cheers, Bert On Thu, Feb 1, 2024 at 4:37?PM TJUN KIAT TEO <teotjunk at hotmail.com> wrote: > Is there a way to extract list of words in BioWordVec in R > > Thank you > > Tjun Kiat > > [[alternative HTML version deleted]] > > ______________________________________________

Is there a way to extract list of words in BioWordVec in R Thank you Tjun Kiat [[alternative HTML version deleted]]

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 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 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

I am trying to do parallel programming and I tried this library(doSNOW) library(foreach) testfunc<-function(x){ x<-x+1 x } noc<-2 cl <- makeCluster(do.call(rbind,rep(list("localhost"),noc)), type = "SOCK") registerDoSNOW(cl) clusterExport(cl=cl,c("testfunc.r")) testl<-foreach(pp=1:2) %dopar% { testfunc(pp) } And this works but if I try to

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) {

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

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

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 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

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

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)

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 =

Hi All It has been suggested to me that the folks in this list might be able to help me out of my misery. As part of my learning curve to building a rather detailed model of a small neurone complex I am implementing some existing models in R. For the moment I want to implement the Izhikevich model as described in his 2003 paper. The equations are as follows: v' = 0.04v^2 + 5v + 140 - u - I

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]]

I am using the package Multicore/Parallel to do importance sampling. I have 5 cores on my computer. And I have let's say 10 000 particles to generate. What I did was to send 5 particles in each time, calling the package parallel. Which means in all I am calling the parallel command 2000 times. What happens is in the end somewhere along the way I end up with the error message error in fork