Tools for Ordinary Differential Equations Model Fitting
Constructor method of "odemodel" class
the initializer for prior.ode
Constructor for solution.ode class
Evaluate the jacobian of the gradients
S4 generic for computing a jacobian
Extract log-likelihood
Class representing log-likelihood models used to fit ode models
Calculate the derivative of the log-likelihood function
Make a list containing log prior density and its gradient
Calculate the derivative of the mean expression
solve ode models
Class "odemodel" representing ode models
Plot a fitode object
Plot a fitodeMCMC object
Internal function for plotting methods
Prediction function for fitode objects
Prediction function for fitodeMCMC objects
Class representing prior models used to fit ode models
Profile fitode objects
Select a log-likelihood model
Select a prior model
Set up link functions for model parameters
Show fitode objects
Show fitodeMCMC object
Show the model
simulate fitode objects
simulate model objects
Internal function for simulation models
Class "solution.ode". Result of solving ode modeld with/without sensit...
Extract standard error from fitode objects
Extract standard error from fitodeMCMC objects
Summarize fitode object
Summarize fitodeMCMC object
Transform the model
Transform the model
Transform the prior model
S4 generic for transforming an object
Update fitode fits
Update fitodeMCMC fits
Extract variance-covariance matrix from fitode objects
Extract variance-covariance matrix from fitodeMCMC objects
Apply link functions to model parameters
Nicholson's blowfly data
Check link functions
Extract model coefficients from fitode objects
Extract model coefficients from fitodeMCMC objects
Calculate confidence intervals from fitode objects for model parameter...
Calculate credible intervals from fitodeMCMC objects for model paramet...
Taylor expansion of digamma(a+b) for a>>b
Taylor expansion of trigamma(a+b) (?) for a>>b
Evaluate the log-likelihood model
S4 generic for evaluating an object
Class "fitode". Result of ode fitting based on Maximum Likelihood Esti...
Fit ordinary differential equations model
Class "fitodeMCMC". Result of ode fitting based on Markov Chain Monte ...
Fit ordinary differential equations model using MCMC
Fix parameters of an ODE model
Evaluate the gradient of a likelihood model
Evaluate the gradients of a model
S4 generic for computing a gradient
S4 generic for computing a hessian
The initializer for loglik.ode
Methods and functions for fitting ordinary differential equations (ODE) model in 'R'. Sensitivity equations are used to compute the gradients of ODE trajectories with respect to underlying parameters, which in turn allows for more stable fitting. Other fitting methods, such as MCMC (Markov chain Monte Carlo), are also available.