7 Example collection

A list of all examples is found on the “Examples” tab on the top of the page.
Locations of example files: adcomp/tmb_examples and adcomp/TMB/inst/examples.
For each example there is both a .cpp and a .R file. Take for instance the linear regression example:

C++ template

// Simple linear regression.
#include <TMB.hpp>
template<class Type>
Type objective_function<Type>::operator() ()
{
  DATA_VECTOR(Y);
  DATA_VECTOR(x);
  PARAMETER(a);
  PARAMETER(b);
  PARAMETER(logSigma);
  ADREPORT(exp(2*logSigma));
  Type nll = -sum(dnorm(Y, a+b*x, exp(logSigma), true));
  return nll;
}

Controlling R code

library(TMB)
compile("linreg.cpp")
dyn.load(dynlib("linreg"))
set.seed(123)
data <- list(Y = rnorm(10) + 1:10, x=1:10)
parameters <- list(a=0, b=0, logSigma=0)
obj <- MakeADFun(data, parameters, DLL="linreg")
obj$hessian <- TRUE
opt <- do.call("optim", obj)
opt
opt$hessian ## <-- FD hessian from optim
obj$he()    ## <-- Analytical hessian
sdreport(obj)

To run this example use the R command
```
source("linreg.R")
```

7.1 Example overview

Example	Description
adaptive_integration.cpp	Adaptive integration using ‘tiny_ad’
ar1_4D.cpp	Separable covariance on 4D lattice with AR1 structure in each direction.
compois.cpp	Conway-Maxwell-Poisson distribution
fft.cpp	Multivariate normal distribution with circulant covariance
hmm.cpp	Inference in a ‘double-well’ stochastic differential equation using HMM filter.
laplace.cpp	Laplace approximation from scratch demonstrated on ‘spatial’ example.
linreg_parallel.cpp	Parallel linear regression.
linreg.cpp	Simple linear regression.
longlinreg.cpp	Linear regression - 10^6 observations.
lr_test.cpp	Illustrate map feature of TMB to perform likelihood ratio tests on a ragged array dataset.
matern.cpp	Gaussian process with Matern covariance.
mvrw_sparse.cpp	Identical with random walk example. Utilizing sparse block structure so efficient when the number of states is high.
mvrw.cpp	Random walk with multivariate correlated increments and measurement noise.
nmix.cpp	nmix example from https://groups.nceas.ucsb.edu/non-linear-modeling/projects/nmix
orange_big.cpp	Scaled up version of the Orange Tree example (5000 latent random variables)
register_atomic_parallel.cpp	Parallel version of ‘register_atomic’
register_atomic.cpp	Similar to example ‘adaptive_integration’ using CppAD Romberg integration. REGISTER_ATOMIC is used to reduce tape size.
sam.cpp	State space assessment model from Nielsen and Berg 2014, Fisheries Research.
sde_linear.cpp	Inference in a linear scalar stochastic differential equation.
sdv_multi_compact.cpp	Compact version of sdv_multi
sdv_multi.cpp	Multivatiate SV model from Skaug and Yu 2013, Comp. Stat & data Analysis (to appear)
socatt.cpp	socatt from ADMB example collection.
spatial.cpp	Spatial poisson GLMM on a grid, with exponentially decaying correlation function
spde_aniso_speedup.cpp	Speedup “spde_aniso.cpp” by moving normalization out of the template.
spde_aniso.cpp	Anisotropic version of “spde.cpp.”
spde.cpp	Illustration SPDE/INLA approach to spatial modelling via Matern correlation function
thetalog.cpp	Theta logistic population model from Pedersen et al 2012, Ecol. Modelling.
TMBad/interpol.cpp	Demonstrate 2D interpolation operator
TMBad/sam.cpp	State space assessment model from Nielsen and Berg 2014, Fisheries Research.
TMBad/solver.cpp	Demonstrate adaptive solver of TMBad
TMBad/spa_gauss.cpp	Demonstrate saddlepoint approximation (SPA)
TMBad/spatial.cpp	Spatial poisson GLMM on a grid, with exponentially decaying correlation function
TMBad/spde_epsilon.cpp	Low-level demonstration of fast epsilon bias correction using ‘sparse plus lowrank’ hessian
TMBad/thetalog.cpp	Theta logistic population model from Pedersen et al 2012, Ecol. Modelling.
transform_parallel.cpp	Parallel version of transform
transform.cpp	Gamma distributed random effects using copulas.
transform2.cpp	Beta distributed random effects using copulas.
tweedie.cpp	Estimating parameters in a Tweedie distribution.
validation/MVRandomWalkValidation.cpp	Estimate and validate a multivariate random walk model with correlated increments and correlated observations.
validation/randomwalkvalidation.cpp	Estimate and validate a random walk model with and without drift
validation/rickervalidation.cpp	Estimate and validate a Ricker model based on data simulated from the logistic map