LVdata                  Example simulated time courses from a
                        stochastic Lotka-Volterra model
StepCLE                 Create a function for advancing the state of an
                        SPN by using a simple Euler-Maruyama
                        integration method for the approximating CLE
StepCLE1D               Create a function for advancing the state of an
                        SPN by using a simple Euler-Maruyama
                        discretisation of the CLE on a 1D regular grid
StepCLE2D               Create a function for advancing the state of an
                        SPN by using a simple Euler-Maruyama
                        discretisation of the CLE on a 2D regular grid
StepEuler               Create a function for advancing the state of an
                        ODE model by using a simple Euler integration
                        method
StepEulerSPN            Create a function for advancing the state of an
                        SPN by using a simple continuous deterministic
                        Euler integration method
StepFRM                 Create a function for advancing the state of an
                        SPN by using Gillespie's first reaction method
StepGillespie           Create a function for advancing the state of an
                        SPN by using the Gillespie algorithm
StepGillespie1D         Create a function for advancing the state of an
                        SPN by using the Gillespie algorithm on a 1D
                        regular grid
StepGillespie2D         Create a function for advancing the state of an
                        SPN by using the Gillespie algorithm on a 2D
                        regular grid
StepODE                 Create a function for advancing the state of an
                        ODE model by using the deSolve package
StepPTS                 Create a function for advancing the state of an
                        SPN by using a simple approximate Poisson time
                        stepping method
StepSDE                 Create a function for advancing the state of an
                        SDE model by using a simple Euler-Maruyama
                        integration method
abcRun                  Run a set of simulations initialised with
                        parameters sampled from a given prior
                        distribution, and compute statistics required
                        for an ABC analaysis
abcSmc                  Run an ABC-SMC algorithm for infering the
                        parameters of a forward model
as.timedData            Convert a time series object to a timed data
                        matrix
discretise              Discretise output from a discrete event
                        simulation algorithm
gillespie               Simulate a sample path from a stochastic
                        kinetic model described by a stochastic Petri
                        net
gillespied              Simulate a sample path from a stochastic
                        kinetic model described by a stochastic Petri
                        net
imdeath                 Simulate a sample path from the homogeneous
                        immigration-death process
mcmcSummary             Summarise and plot tabular MCMC output
metrop                  Run a simple Metropolis sampler with standard
                        normal target and uniform innovations
metropolisHastings      Run a Metropolis-Hastings MCMC algorithm for
                        the parameters of a Bayesian posterior
                        distribution
mytable                 Simple example data frame
normgibbs               A simple Gibbs sampler for Bayesian inference
                        for the mean and precision of a normal random
                        sample
pfMLLik                 Create a function for computing the log of an
                        unbiased estimate of marginal likelihood of a
                        time course data set
pfMLLik1                Create a function for computing the log of an
                        unbiased estimate of marginal likelihood of a
                        time course data set
rcfmc                   Simulate a continuous time finite state space
                        Markov chain
rdiff                   Simulate a sample path from a univariate
                        diffusion process
rfmc                    Simulate a finite state space Markov chain
simSample               Simulate a many realisations of a model at a
                        given fixed time in the future given an initial
                        time and state, using a function (closure) for
                        advancing the state of the model
simTimes                Simulate a model at a specified set of times,
                        using a function (closure) for advancing the
                        state of the model
simTs                   Simulate a model on a regular grid of times,
                        using a function (closure) for advancing the
                        state of the model
simTs1D                 Simulate a model on a regular grid of times,
                        using a function (closure) for advancing the
                        state of the model
simTs2D                 Simulate a model on a regular grid of times,
                        using a function (closure) for advancing the
                        state of the model
simpleEuler             Simulate a sample path from an ODE model
smfsb                   Stochastic Modelling for Systems Biology
spnModels               Example SPN models
stepLVc                 A function for advancing the state of a
                        Lotka-Volterra model by using the Gillespie
                        algorithm
