added REML example to "TMB_examples"

TMB examples/REML/REML.R

@@ -0,0 +1,62 @@
+
+setwd( "C:/Users/James.Thorson/Desktop/Project_git/2018_FSH556/TMB examples/REML" )
+#devtools::install_github("kaskr/TMB_contrib_R/TMBhelper")
+
+library(lme4)
+library(TMB)
+
+# Compile model
+Version = "REML"
+compile( paste0(Version,".cpp") )
+dyn.load( dynlib("REML") )
+
+######################
+# Simulate data
+######################
+
+# Simulate predictors
+group_i = rep( 1:10, each=10)
+z_g = rnorm( length(unique(group_i)), mean=0, sd=1)
+beta0 = 0
+
+# Simulate response
+y_i = z_g[group_i] + beta0 + rnorm( length(group_i), mean=0, sd=1)
+
+######################
+# Run WITHOUT REML in R and TMB
+######################
+
+# In R
+Lme_noREML = lmer( y_i ~ 1|factor(group_i), REML=FALSE)
+
+# In TMB
+Data = list( "n_groups"=length(unique(group_i)), "g_i"=group_i-1, "y_i"=y_i)
+Parameters = list( "beta0"=-10, "log_SD0"=2, "log_SDZ"=2, "z_g"=rep(0,Data$n_groups) )
+Random = c("z_g")
+Obj = MakeADFun(data=Data, parameters=Parameters, random=Random)  #
+Opt_noREML = TMBhelper::Optimize( obj=Obj, newtonsteps=1 )
+
+# TMB
+exp(Opt_noREML$par['log_SDZ'])
+# R
+summary(Lme_noREML)
+
+######################
+# Run WITH REML in R and TMB
+######################
+
+# In R
+Lme_REML = lmer( y_i ~ 1|factor(group_i), REML=TRUE)
+
+# In TMB
+Data = list( "n_groups"=length(unique(group_i)), "g_i"=group_i-1, "y_i"=y_i)
+Parameters = list( "beta0"=-10, "log_SD0"=2, "log_SDZ"=2, "z_g"=rep(0,Data$n_groups) )
+Random = c("z_g","beta0")
+Obj = MakeADFun(data=Data, parameters=Parameters, random=Random)  #
+Opt_REML = TMBhelper::Optimize( obj=Obj, newtonsteps=1 )
+
+# TMB
+exp(Opt_REML$par['log_SDZ'])
+# R
+summary(Lme_REML)
+

TMB examples/REML/REML.cpp

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+#include <TMB.hpp>
+template<class Type>
+Type objective_function<Type>::operator() ()
+{
+  // Data
+  DATA_INTEGER( n_groups );
+  DATA_IVECTOR( g_i );
+  DATA_VECTOR( y_i );
+
+  // Parameters
+  PARAMETER( beta0 );
+  PARAMETER( log_SD0 );
+  PARAMETER( log_SDZ );
+  PARAMETER_VECTOR( z_g );
+
+  // Objective funcction
+  Type jnll = 0;
+  int n_i = y_i.size();
+
+  // Probability of data conditional on fixed and random effect values
+  for( int i=0; i<n_i; i++){
+    jnll -= dnorm( y_i(i), beta0 + z_g(g_i(i)), exp(log_SD0), true );
+  }
+
+  // Probability of random coefficients
+  for( int g=0; g<n_groups; g++){
+    jnll -= dnorm( z_g(g), Type(0.0), exp(log_SDZ), true );
+  }
+
+  // Reporting
+  Type SDZ = exp(log_SDZ);
+  Type SD0 = exp(log_SD0);
+
+  REPORT( SDZ );
+  REPORT( SD0 );
+  ADREPORT( SDZ );
+  ADREPORT( SD0 );
+
+  return jnll;
+}