X-Git-Url: https://git.auder.net/?p=morpheus.git;a=blobdiff_plain;f=pkg%2FR%2FoptimParams.R;h=039070c5280b847af077056b2cfcc89b6c73b589;hp=13aec835f3a39e9060b6d080e10913ea3f121403;hb=2591fa8343c69ddb94dec5e55871d34c55eff9a3;hpb=074c721aa587d45c4f7ef10f8a28fdc09273d31a

diff --git a/pkg/R/optimParams.R b/pkg/R/optimParams.R
index 13aec83..039070c 100644
--- a/pkg/R/optimParams.R
+++ b/pkg/R/optimParams.R
@@ -31,7 +31,7 @@
 #' o$f( o$linArgs(par0) )
 #' o$f( o$linArgs(par1) )
 #' @export
-optimParams <- function(X, Y, K, link=c("logit","probit"))
+optimParams <- function(X, Y, K, link=c("logit","probit"), M=NULL)
 {
   # Check arguments
   if (!is.matrix(X) || any(is.na(X)))
@@ -42,9 +42,21 @@ optimParams <- function(X, Y, K, link=c("logit","probit"))
   if (!is.numeric(K) || K!=floor(K) || K < 2)
     stop("K: integer >= 2")
 
+  if (is.null(M))
+  {
+    # Precompute empirical moments
+    Mtmp <- computeMoments(X, Y)
+    M1 <- as.double(Mtmp[[1]])
+    M2 <- as.double(Mtmp[[2]])
+    M3 <- as.double(Mtmp[[3]])
+    M <- c(M1, M2, M3)
+  }
+  else
+    M <- c(M[[1]], M[[2]], M[[3]])
+
   # Build and return optimization algorithm object
   methods::new("OptimParams", "li"=link, "X"=X,
-    "Y"=as.integer(Y), "K"=as.integer(K))
+    "Y"=as.integer(Y), "K"=as.integer(K), "Mhat"=as.double(M))
 }
 
 #' Encapsulated optimization for p (proportions), β and b (regression parameters)
@@ -82,19 +94,15 @@ setRefClass(
       "Check args and initialize K, d, W"
 
       callSuper(...)
-      if (!hasArg("X") || !hasArg("Y") || !hasArg("K") || !hasArg("li"))
+      if (!hasArg("X") || !hasArg("Y") || !hasArg("K")
+        || !hasArg("li") || !hasArg("Mhat"))
+      {
         stop("Missing arguments")
-
-      # Precompute empirical moments
-      M <- computeMoments(X, Y)
-      M1 <- as.double(M[[1]])
-      M2 <- as.double(M[[2]])
-      M3 <- as.double(M[[3]])
-      Mhat <<- c(M1, M2, M3)
+      }
 
       n <<- nrow(X)
-      d <<- length(M1)
-      W <<- diag(d+d^2+d^3) #initialize at W = Identity
+      d <<- ncol(X)
+      # W will be initialized when calling run()
     },
 
     expArgs = function(v)
@@ -256,17 +264,24 @@ setRefClass(
         θ0$b = rep(0, K)
       else if (!is.numeric(θ0$b) || length(θ0$b) != K || any(is.na(θ0$b)))
         stop("θ0$b: length K, no NA")
-      # TODO: stopping condition? N iterations? Delta <= epsilon ?
-      for (loop in 1:2)
+
+      # (Re)Set W to identity, to allow several run from the same object
+      W <<- diag(d+d^2+d^3)
+
+      loopMax <- 2 #TODO: loopMax = 3 ? Seems not improving...
+      x_init <- linArgs(θ0)
+      for (loop in 1:loopMax)
       {
-        op_res = constrOptim( linArgs(θ0), .self$f, .self$grad_f,
+        op_res = constrOptim( x_init, .self$f, .self$grad_f,
           ui=cbind(
             rbind( rep(-1,K-1), diag(K-1) ),
             matrix(0, nrow=K, ncol=(d+1)*K) ),
           ci=c(-1,rep(0,K-1)) )
-        W <<- computeW(expArgs(op_res$par))
-        print(op_res$value) #debug
-        print(expArgs(op_res$par)) #debug
+        if (loop < loopMax) #avoid computing an extra W
+          W <<- computeW(expArgs(op_res$par))
+        x_init <- op_res$par
+        #print(op_res$value) #debug
+        #print(expArgs(op_res$par)) #debug
       }
 
       expArgs(op_res$par)