Getting started

This part of the documentation gets you started with using Chi. Each section gives a brief introduction into the modelling framework and shows examples of how to implement models in Chi. The covered topics include simulation and inference of e.g. ODE models, PKPD models with drug administration and non-linear mixed effects models / hierarchical models.

Table of Contents

• 1. Quick overview
  • 1.1. Simulating a mechanistic model
  • 1.2. Visualisation of the simulation
  • 1.3. Simulation of measurements
  • 1.4. Inference of model parameters
  • 1.5. Simulating a population model
  • 1.6. Hierarchical inference
• 2. The mechanistic model
  • 2.1. Defining mechanistic models using the MechanisticModel interface
  • 2.2. Defining mechanistic models using SBML files
  • 2.3. Reference to MechanisticModel API
• 3. Fitting mechanistic models to data
  • 3.1. Estimating model parameters from data: Background
  • 3.2. Defining the log-posterior
  • 3.3. Inferring the posterior distribution
  • 3.4. Assessing convergence: Summary
  • 3.5. Comparing model fits to data
  • 3.6. Reference to ErrorModel, LogPDF and PredictiveModel API