chapter 1 Getting started with Ad Model Builder

  • section 1 Example 1 -- linear least-squares
  • section 2 The DATA SECTION
  • section 3 The Parameter Section
  • section 4 The Procedure Section
  • section 5 The Preliminary Calcs Section
  • section 6 The use of loops and element-wise operations
  • section 7 The default output from AD Model Builder
  • section 8 Robust Nonlinear regression with AD Model Builder
  • section 9 Modifying the model to use robust nonlinear regression
  • section 10 Chemical engineering -- a chemical kinetics problem
  • section 11 Financial Modelling -- A Generalized Autoregressive Conditional hboxHeteroskedasticity or GARCH model
  • section 12 Carrying out the minimization in a number of phases
  • section 13 Natural resource management -- the Schaeffer-Pella-Tomlinson Model
  • section 14 Bayesian considerations in the Pella--Tomlinson model
  • section 15 Using FUNCTIONS to improve code organization
  • section 16 A fisheries catch-at-age model
  • section 17 Bayesian inference and the profile likelihood
  • section 18 Modifying the approximation of the profile likelihood
  • section 19 Changing the default file names for data and parameter input
  • section 20 Using the subvector operation to avoid writing loops
  • section 21 The use of higher dimensional arrays
  • section 22 The TOP_OF_MAIN section
  • section 23 The GLOBALS_SECTION
  • section 24 The BETWEEN_PHASES_SECTION
  • chapter 2 Markov Chain Simulation

  • section 1 Introduction to the Markov Chain Monte Carlo approach in Bayesian Anaylsis
  • section 2 Reading AD Model Builder binary files
  • chapter 3 A forestry model -- estimating the size distribution of wildfires

  • section 1 Model description
  • section 2 The numerical integration routine
  • section 3 Using the ad_begin_funnel routine to reduce the amount of temporary storage required
  • section 4 Effect of the accuracy switch on the running time for numerical integration
  • section 5 A comparison with Splus for the forestry model
  • chapter 4 Macro Economics Modeling with AD Model Builder

  • section 1 Anaylsis of economic data from Hamilton's 1989 paper
  • section 2 The code for Hamilton's fourth order autoregressive model
  • section 3 Results of the analysis
  • section 4 Extending Hamilton's model to a fifth order autoregressive process
  • chapter 5 Advanced Features of AD Model Builder

  • section 1 Using other class libraries in AD Model Builder programs
  • section 2 Appendix 1 -- The regression function
  • section 3 Appendix 2 -- AD Model Builder types
  • section 4 References
  • section 5 How to order AD Model Builder