small changes to Week 7 lab

Week 7 -- spatiotemporal models/Lab/Sim_Gompertz_Fn.R

@@ -37,5 +37,6 @@ function( n_years, n_stations=100, phi=NULL, SpatialScale=0.1, SD_O=0.5, SD_E=0.
 
   # Return stuff
   Sim_List = list("DF"=DF, "phi"=phi, "Loc"=Loc, "Omega"=Omega, "Epsilon"=Epsilon, "Theta"=Theta)
+  Sim_List[["Parameters"]] = c('SpatialScale'=SpatialScale, 'SigmaO'=SD_O, 'SigmaE'=SD_E, 'rho'=rho, 'phi'=phi)
   return(Sim_List)
 }

Week 7 -- spatiotemporal models/Lab/spatial_gompertz.cpp

@@ -78,7 +78,7 @@ Type objective_function<Type>::operator() ()
   // Likelihood contribution from observations
   vector<Type> log_chat_i(n_i);
   for (int i=0; i<n_i; i++){
-    log_chat_i(i) = phi*pow(rho,t_i(i)) + Epsilon_xt(x_s(s_i(i)),t_i(i)) + (eta_x(x_s(s_i(i))) + Omega_x(x_s(s_i(i))) ) / (1-rho);
+    log_chat_i(i) = phi*pow(rho,t_i(i)) + (eta_x(x_s(s_i(i))) + Omega_x(x_s(s_i(i)) + Epsilon_xt(x_s(s_i(i)),t_i(i))) ) / (1-rho);
     if( !isNA(c_i(i)) ){
       jnll_comp(2) -= dpois( c_i(i), exp(log_chat_i(i)), true );
     }
@@ -100,6 +100,7 @@ Type objective_function<Type>::operator() ()
   REPORT( Epsilon_xt );
   REPORT( Omega_x );
   REPORT( Equil_x );
+  REPORT( phi );
 
   return jnll;
 }

Week 7 -- spatiotemporal models/Lab/spatial_gompertz_estimation_example.R

@@ -1,6 +1,6 @@
 
 
-setwd( "C:/Users/James.Thorson/Desktop/Project_git/2016_classes_private/Spatio-temporal models/Week 7 -- spatiotemporal models/Lab" )
+setwd( "C:/Users/James.Thorson/Desktop/Project_git/2018_FSH556/Week 7 -- spatiotemporal models/Lab" )
 
 #########################
 # Spatial Gompertz model
@@ -11,12 +11,11 @@ setwd( "C:/Users/James.Thorson/Desktop/Project_git/2016_classes_private/Spatio-t
 library(INLA)
 library(TMB)
 library(RandomFields)
-library(TMBdebug)
 
 source( "Sim_Gompertz_Fn.R" )
 
 # Read data
-# n_years=10; n_stations=100; SpatialScale=0.1; SD_O=0.5; SD_E=0.2; SD_extra=0; rho=0.8; logMeanDens=1; phi=NULL; Loc=NULL
+set.seed( 2 )
 Sim_List = Sim_Gompertz_Fn( n_years=10, n_stations=100, SpatialScale=0.1, SD_O=0.4, SD_E=0.2, SD_extra=0, rho=0.5, logMeanDens=1, phi=0.0, Loc=NULL )
 DF = Sim_List[["DF"]]
 loc_xy_orig = loc_xy = Sim_List[["Loc"]]
@@ -32,7 +31,7 @@ if( n_knots < nrow(loc_xy) ){
 }
 
 plot( loc_xy_orig, cex=2, pch=20 )
-points( loc_xy, cex=2, pch=20, col="red")
+points( loc_xy, cex=2, pch=3, col="red")
 
 # Build SPDE object using INLA (must pass mesh$idx$loc when supplying Boundary)
 mesh = inla.mesh.create( loc_xy )
@@ -43,10 +42,15 @@ spde = inla.spde2.matern( mesh )
 
 
 ###################
+#
 # Parameter estimation
+#
 ###################
 
-#####  Version 0 -- Sweep upstream to downstream through time
+#####################
+#  Version 0 -- Sweep upstream to downstream through time
+#####################
+
 Version = "spatial_gompertz_state_as_random"
 
 # Compile
@@ -60,19 +64,19 @@ Parameters = list(alpha=c(0.0), phi=0.0, log_tau_U=1.0, log_tau_O=1.0, log_kappa
 Random = c("log_D_xt","Omega_input")
 
 # Make object
-obj <- MakeADFun(data=Data, parameters=Parameters, random=Random, hessian=FALSE, DLL=Version)
+Obj = MakeADFun(data=Data, parameters=Parameters, random=Random, hessian=FALSE, DLL=Version)
 
 # Run optimizer
-start_time = Sys.time()
-opt0 = nlminb(obj$par, objective=obj$fn, gradient=obj$gr, lower=c(rep(-20,2),rep(-10,3),-0.999), upper=c(rep(20,2),rep(10,3),0.999), control=list(eval.max=1e4, iter.max=1e4, trace=1))
-opt0[["final_gradient"]] = obj$gr( opt0$par )
-opt0[["total_time"]] = Sys.time() - start_time
+Opt0 = TMBhelper::Optimize( obj=Obj, lower=c(rep(-Inf,5),-0.999), upper=c(rep(Inf,5),0.999), getsd=TRUE, newtonsteps=1 )
 
 # Get standard errors
-Report0 = obj$report()
-SD0 = try( sdreport(obj) )
+Report0 = Obj$report()
+H0 = Obj$env$spHess()
+
+##################
+#  Version 3 -- Joint analysis using TMB functions
+##################
 
-#####  Version 3 -- Joint analysis using TMB functions
 Version = "spatial_gompertz"
 
 # Compile
@@ -86,21 +90,32 @@ Parameters = list(alpha=c(0.0), phi=0.0, log_tau_E=1.0, log_tau_O=1.0, log_kappa
 Random = c("Epsilon_input","Omega_input")
 
 # Make object
-obj <- MakeADFun(data=Data, parameters=Parameters, random=Random, hessian=FALSE, DLL=Version)
+Obj <- MakeADFun(data=Data, parameters=Parameters, random=Random, hessian=FALSE, DLL=Version)
 
 # Run optimizer
-start_time = Sys.time()
-opt3 = nlminb(obj$par, objective=obj$fn, gradient=obj$gr, lower=c(rep(-20,2),rep(-10,3),-0.999), upper=c(rep(20,2),rep(10,3),0.999), control=list(eval.max=1e4, iter.max=1e4, trace=1))
-opt3[["final_gradient"]] = obj$gr( opt3$par )
-opt3[["total_time"]] = Sys.time() - start_time
+Opt3 = TMBhelper::Optimize( obj=Obj, lower=c(rep(-Inf,5),-0.999), upper=c(rep(Inf,5),0.999), getsd=TRUE, newtonsteps=1 )
 
 # Get standard errors
-Report3 = obj$report()
-SD3 = try( sdreport(obj) )
+Report3 = Obj$report()
+H3 = Obj$env$spHess()
 
 ######## Compare results
 
-# Report
-unlist( Report0[c('Range','SigmaO','SigmaU','SigmaE','rho')] )
-unlist( Report3[c('Range','SigmaO','SigmaU','SigmaE','rho')] )
+# Check parameter estimates
+unlist(Report0[c('Range','SigmaO','SigmaU','rho','phi')])
+unlist(Report3[c('Range','SigmaO','SigmaE','rho','phi')])
+Sim_List[["Parameters"]][c('SpatialScale','SigmaO','SigmaE','rho','phi')]
+
+# Compare sparseness
+sum( H0!=0 ) / prod(dim(H0))
+sum( H3!=0 ) / prod(dim(H0))
+
+# Show inner hessian
+image( H0, main="Version0: Sweep through time" );
+dev.new(); image(H3, main="Version3: TMB functions")
+
+# Run times
+Opt0$run_time
+Opt3$run_time
+
 

Week 7 -- spatiotemporal models/Lab/spatial_gompertz_state_as_random.cpp

@@ -109,6 +109,7 @@ Type objective_function<Type>::operator() ()
   REPORT( log_Dpred_xt );
   REPORT( Omega_x );
   REPORT( Equil_x );
+  REPORT( phi );
 
   return jnll;
 }