similar to: Differential Equations there use in R (population modeling)

Hi, I am performing a repeated measures 2-way ANOVA to assess the influence of plant and leaf on aphid fecundity. Fecundity is measured for each aphid on a single leaf. Here is what I typed. wingless <- reshape(Wingless, varying =

Hi, I need to analyze the influences of several factors on a variable that is a measure of fecundity, consisting of 73 observations ranging from 0 to 5. The variable is continuous and highly positive skewed, none of the typical transformations was able to normalize the data. Thus, I was thinking in analyzing these data using a generalized linear model where I can specify a distribution other than

hello everyone, I would like to as for advice for the use of ?lmer? (package ?lme4?) and writing the proper syntax to best describe my data using a mixed-effects model. I have just started to use these models, and although I have read some good examples (Extending the Linear Model with R, Faraway 2005; and the R book, Crawley 2007), I am still not sure of the syntax to test my hypothesis.

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

Hello List, Can you recommend me if odeSolve can handle stiff delay differential equations with discontinuities? Or any other package? Best, -m

I need to solve a system of non-linear fourth-order differential equations. Is there a command which solves this system? Thanks in advance.

Dear all, I wonder if there is a way to specify a model in differential equations for nlme(). Or in other packages? Appreciate any comment. Thanks. Jun Shen [[alternative HTML version deleted]]

Hello list I have a theoretical differential equation model (two coupled differential equations) describing the acidification of dairy cultures in milk: dX/dt = f(H, param)*X dH/dt = g(param)*dX/dt pH = -log10(H) I also have actual data of the same. I would like to estimate the parameters of the theoretical model from real data, but don't know how to go about it in R (I'm fairly new

Dear R-users, I am trying to perform some simulations from a model defined by ordinary differential equations. I would be grateful if someone could indicate some functions/packages/examples I could look at. Thank you in advance. Sebastien

Is there any R code available for solving ODE's? I am considering building an interface to ODEPACK, but don't want to duplicate any existing effort. -- Tom Wainwright NOAA/NMFS/NWFSC 2030 S Marine Science Dr Newport, OR 97365 USA thomas.wainwright at noaa.gov -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

> On Jun 21, 2017, at 12:48 PM, Marine Regis <marine.regis at hotmail.fr> wrote: > > 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

Dear R-community My ODE problems looks as follows: (1) dA/dt = u*A - v*B (2) dB/dt = v*B - u*A where u is a constant, and v=k*t (k=constant, t=time) Does anybody knows a good function/procedure of solving? Should one involve the equation (3) dv/dt = k? Thanks for your support. -- Dominik Heinzmann Master of Science in Mathematics, EPFL Ph.D. student in Biostatistics Institute of Mathematics

Hello everyone, I am trying to solve 2D differential equations using finite difference scheme in R. I have been able to work with the equations with only one spatial dimensions but I want to extend it to the two dimensional problem. For example i can simulate one dimensional diffusion using a code like the following. But I want to write a similar code for,say, a two dimensional diffusion

Dear All,   Currently I am running the following code:   library(stats4) library(odesolve) library(rgenoud) Input<-data.frame(SUB=c(1),time=c(0.5,3,10,15),lev=c(2.05,12.08,9.02,8)) XD<-500 IT<-3 diffeqfun<-function(time, y, parms) {   if(time<=IT)      dCpdt <- (XD/IT)/parms["Vol"] -

It seems that the method `iteration` in the function `ode` can be useful in my case: > Method "iteration" is special in that here the function func should > return the new value of the state variables rather than the rate of > change. This can be used for individual based models, for difference > equations, or in those cases where the integration is performed within >

Hi all, My apologies if this message is incredibly inept but I am very new to both computer programming and to R. I am working with the odesolve add-on and have the following function defined RVF_Single <- function(t, x, p) within the script I also have the following functions defined: T1<-function(t) {T1<-27.5-12.5*cos(2*pi*t/365)} and B1<-function(T1,t)

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)

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

To whom it may concern, I am a student at Macaleste College, and next semester Macalester is going to offer a course for CellBio that is mainly statistically based. For the most part the students will be using R for analysis. The problem is there will be some simple differential equations for the students to solve. The committee that in charge of the classes corriculam would like only to

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