pymb-test-script.py

import numpy as np
import PyMB

# create an empty model
m = PyMB.model(name='linreg')

# code for a simple linear regression
linreg_code = '''
#include <TMB.hpp>
template<class Type>
Type objective_function<Type>::operator() (){
// DATA
  DATA_VECTOR(Y);
  DATA_VECTOR(x);

// PARAMETERS
  PARAMETER(alpha);
  PARAMETER(Beta);
  PARAMETER(logSigma);

// MODEL
  vector<Type> Y_hat = alpha + Beta*x;
  REPORT(Y_hat);
  Type nll = -sum(dnorm(Y, Y_hat, exp(logSigma), true));
  return nll;
}
'''

# compile the model using defaults
m.compile(codestr=linreg_code)

# simulate data
m.data['x'] = np.arange(10)
m.data['Y'] = m.data['x'] + 0.5 + np.random.rand(10)

# set initial parameter values
m.init['alpha'] = 0.
m.init['Beta'] = 0.
m.init['logSigma'] = 0.

# set random parameters
m.random = ['alpha', 'Beta']

# fit the model
m.optimize()
print(m.report('Y_hat'))