simode

simode: R Package for Statistical Inference of Ordinary Differential Equations using Separable Integral-Matching - Published in JOSS (2019)

https://github.com/ramiyaari/simode

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simode: R Package for statistical inference of ordinary differential equations using separable integral-matching

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  • Host: GitHub
  • Owner: ramiyaari
  • License: gpl-2.0
  • Language: R
  • Default Branch: master
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Created over 7 years ago · Last pushed almost 6 years ago
Metadata Files
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README.md

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version DOI joss

simode v1.1.9:

An R package for conducting statistical inference for ordinary differential equations that aims to ease the optimization process and provide more robust solutions to parameter estimation problems. See, Dattner and Klassen (2015) and Dattner et al. (2017).

Getting Started:

From an R console, type install.packages('simode') to install the package. After download is complete type library('simode') to load the package.

Example usage:

Following is an example of usage of the package using the Lotka-Volterra Predator-Prey model.

```R

generate model equations and parameters (X=Prey,Y=Predator)

pars <- c('alpha','beta','gamma','delta') vars <- c('X','Y') eqX <- 'alphaX-betaX*Y' eqY <- 'deltaXY-gamma*Y' equations <- c(eqX,eqY) names(equations) <- vars x0 <- c(0.9,0.9) names(x0) <- vars theta <- c(2/3,4/3,1,1) names(theta) <- pars

generate observations

n <- 50 time <- seq(0,25,length.out=n) modelout <- solveode(equations,theta,x0,time) xdet <- modelout[,vars] set.seed(1000) sigma <- 0.05 obs <- list() for(i in 1:length(vars)) { obs[[i]] <- pmax(0, rnorm(n,x_det[,i],sigma)) } names(obs) <- vars

estimate model parameters with known initial conditions

simodefit1 <- simode(equations=equations, pars=pars, fixed=x0, time=time, obs=obs) plot(simodefit1, type='fit', time=seq(0,25,length.out=100), parstrue=theta, mfrow=c(2,1)) plot(simodefit1, type='est', pars_true=theta)

estimate model parameters and initial conditions

simodefit2 <- simode(equations=equations, pars=c(pars,vars), time=time, obs=obs) plot(simodefit2, type='fit', time=seq(0,25,length.out=100), parstrue=c(theta,x0), mfrow=c(2,1)) plot(simodefit2, type='est', pars_true=c(theta,x0))

profilesfit2 <- profile(simodefit2,stepsize=0.01,maxsteps=50) plot(profilesfit2,mfrow=c(2,3)) cifit2 <- confint(profilesfit2) cifit2 plot(cifit2,parstrue=c(theta,x0),legend=TRUE) ```

More examples can be found as demos inside the package (type: demo(package='simode'))

Documentation:

From an R console type ?simode for help on the package. The package page at CRAN is [here], package reference manual is [here], package vignette is [here].

Support and Contributions:

For support and bug reports send an email to: ramiyaari@gmail.com or open an issue [here]. Code contributions to simode are also very welcome.

References:

Dattner Itai, Klaassen Chris. Optimal rate of direct estimators in systems of ordinary differential equations linear in functions of the parameters. Electonic Journal of Statistics, 9(2), 2015. [link]

Dattner Itai, Miller Ezer, Petrenko Margarita, Kadouri Daniel, Jurkevitch Edouard and Huppert Amit. Modelling and parameter inference of predator–prey dynamics in heterogeneous environments using the direct integral approach. Journal of the Royal Society Interface, 14(126), 2017. [link].

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JOSS Publication

simode: R Package for Statistical Inference of Ordinary Differential Equations using Separable Integral-Matching
Published
December 22, 2019
Volume 4, Issue 44, Page 1850
Authors
Rami Yaari
Department of Statistics, University of Haifa, Haifa, 34988, Israel, Bio-statistical and Bio-mathematical Unit, The Gertner Institute for Epidemiology and Health Policy Research, Chaim Sheba Medical Center, Tel Hashomer, 52621, Israel
Itai Dattner
Department of Statistics, University of Haifa, Haifa, 34988, Israel
Editor
Matthew Sottile ORCID
Tags
dynamic systems ordinary differential equations statistical inference integral-matching separable least-squares

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