added support for initial values

- function_signatures::add supports up to 7 arguments
- stan::prob::propto supports up to 10 arguments
- update dlm examples in src/models/misc/dlm/

Conflicts:
	src/models/misc/dlm/fx_equicorr.stan
	src/models/misc/dlm/fx_factor.stan

Author: jrnold

misc/dlm/create_fx_equicorr_data.R

@@ -0,0 +1,14 @@
+library(rstan)
+load("fxrates.rda")
+
+standata <-
+  within(list(), {
+    y <- t(fxrates)
+    r <- nrow(y)
+    T <- ncol(y)
+    m0 <- array(rep(0, r), r)
+    C0 <- diag(3) * 1e7
+  })
+
+
+stan_rdump(names(standata), file="fx_equicorr.data.R", envir=as.environment(standata))

misc/dlm/create_fx_factor_data.R

@@ -0,0 +1,14 @@
+library(rstan)
+load("fxrates.rda")
+
+standata <-
+  within(list(), {
+    y <- t(fxrates)
+    r <- nrow(y)
+    T <- ncol(y)
+    m0 <- array(0, 1)
+    C0 <- matrix(1e7)
+  })
+
+
+stan_rdump(names(standata), file="fx_factor.data.R", envir=as.environment(standata))

misc/dlm/fx.data.R

@@ -1,4 +1,5 @@
-n <- 3
+r <- 3
+n <- 1
 T <- 2465
 y <- 
 structure(c(-0.0156963885668762, -0.081740713395602, -0.0281008463968755,

misc/dlm/fx_equicorr.stan

@@ -1,28 +1,30 @@
 data {
-  int n;
+  int r;
   int T;
-  matrix[n, T] y;
+  matrix[r, T] y;
+  vector[r] m0;
+  cov_matrix[r] C0;
 }
 transformed data {
-  vector[n] ones;
-  matrix[n, n] G;
-  matrix[n, n] F;
-  for (i in 1:n) {
+  vector[r] ones;
+  matrix[r, r] G;
+  matrix[r, r] F;
+  for (i in 1:r) {
     ones[i] <- 1.0;
   }
   G <- diag_matrix(ones);
   F <- G;
 }
 parameters {
   real<lower=-1.0, upper=1.0> rho;
-  vector<lower=0.0>[n] sigma;
-  vector<lower=0.0>[n] W_diag;
+  vector<lower=0.0>[r] sigma;
+  vector<lower=0.0>[r] W_diag;
 }
 transformed parameters {
-  cov_matrix[n] V;
-  cov_matrix[n] W;
+  cov_matrix[r] V;
+  cov_matrix[r] W;
   W <- diag_matrix(W_diag);
-  for (i in 1:n) {
+  for (i in 1:r) {
     V[i, i] <- pow(sigma[i], 2);
     for (j in 1:(i - 1)) {
       V[i, j] <- sigma[i] * sigma[j] * rho;
@@ -31,5 +33,5 @@ transformed parameters {
   }
 }
 model {
-  y ~ gaussian_dlm_log(F, G, V, W);
+  y ~ gaussian_dlm_log(F, G, V, W, m0, C0);
 }

misc/dlm/fx_factor.data.R

@@ -5,6 +5,8 @@ data {
   int r;
   int T;
   matrix[r, T] y;
+  vector[1] m0;
+  cov_matrix[1] C0;
 }
 transformed data {
   matrix[1, 1] G;
@@ -22,5 +24,5 @@ transformed parameters {
   }
 }
 model {
-  y ~ gaussian_dlm(F, G, V, W);
+  y ~ gaussian_dlm(F, G, V, W, m0, C0);
 }