Introduction | Notation | Stochastic State Space System | Observations and Likelihood | What is a "Prediction"? | Moment Differential Equations | Algorithm | Example | Create Model | Create Data using Simulate | Predict | Output | Long prediction horizons | Forecast Evaluation

Introduction | Notation | Stochastic State Space System | Observations and Likelihood | What is a "Simulation"? | Algorithm \label | Example | Create Model | Create Data | Simulate | Output | Estimating with the Simulated Observations | Many Simulations | Increasing Process Noise | Distribution Plot | Method Arguments | pars | method | ode.solver | ode.timestep | k.ahead | return.k.ahead | sim.timestep | n.sims | initial.state | estimate.initial.state | silent

Notation | General Idea | Setup | Details

Initialising | Add system equations | Add observation equations | Add observation variances | Add inputs | Add parameters | Set initial state and covariance | Generate Data | Perform estimation | Inspecting the fit object | Parameter estimates | State estimates | Residual analysis | Profiling the likelihood | Extra: Algebraic equations

Introduction | Notation | Stochastic State Space System | Observations and Likelihood | What is an "Estimation"? | Moment Differential Equations | Example | Method Arguments | method | ode.solver | ode.timestep | loss / loss_c | use_hessian | laplace.residuals | unconstrainted.optim | estimate.initial.state | control | silent

Simulate from the Ornstein-Uhlenbeck process | Construct model object | Estimation | Extract function handlers | Extract parameter lower/upper bounds | Optimize manually using stats::optim | Compare results between the two optimizers

Adding observation equations | Adding observation variances | Multiple observation equations