[Yuima-commits] r378 - pkg/yuima/R

[noreply at r-forge.r-project.org]

Author: iacus
Date: 2015-04-26 15:27:51 +0200 (Sun, 26 Apr 2015)
New Revision: 378

Modified:
   pkg/yuima/R/WoodChanfGn.R
   pkg/yuima/R/adaBayes.R
   pkg/yuima/R/asymptotic_term_second.R
   pkg/yuima/R/asymptotic_term_third.R
   pkg/yuima/R/asymptotic_term_third_function.R
   pkg/yuima/R/cogarchNoise.R
   pkg/yuima/R/lse.R
   pkg/yuima/R/qgv.R
   pkg/yuima/R/simFunctional.R
   pkg/yuima/R/yuima.model.R
Log:
update

Modified: pkg/yuima/R/WoodChanfGn.R
===================================================================
--- pkg/yuima/R/WoodChanfGn.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/WoodChanfGn.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -57,7 +57,7 @@
 	
 	
 #Traitement des zeros	
-#La matrice est définie positive (voir 17)	
+#La matrice est definie positive (voir 17)	
 	
 return(fGn)
 		

Modified: pkg/yuima/R/adaBayes.R
===================================================================
--- pkg/yuima/R/adaBayes.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/adaBayes.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -239,7 +239,7 @@
 	 HaveDiffHess <- FALSE
 	 if(length(start)){
 #		if(JointOptim){ ### joint optimization
-#			if(length(start)>1){ #Â?multidimensional optim
+#			if(length(start)>1){ #multidimensional optim
 #				oout <- optim(start, fj, method = method, hessian = TRUE, lower=lower, upper=upper)
 #				HESS <- oout$hessian
 #				HaveDriftHess <- TRUE
Modified: pkg/yuima/R/asymptotic_term_second.R
===================================================================
--- pkg/yuima/R/asymptotic_term_second.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/asymptotic_term_second.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -964,7 +964,7 @@
 	get_Y_e_V <- Y_e_V(X.t0,de.diffusion,env)
 
 	mu <- funcmu(env=env)
-	aMat <- funca(env=env)   ## ¤³¤³¤Ç¥¨¥é¡¼ 2010/11/24, TBC
+	aMat <- funca(env=env)   ## 2010/11/24, TBC
 	Sigma <- funcsigma(env=env)
 
 	invSigma <- solve(Sigma)
Modified: pkg/yuima/R/asymptotic_term_third.R
===================================================================
--- pkg/yuima/R/asymptotic_term_third.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/asymptotic_term_third.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -1035,7 +1035,7 @@
 	get_Y_e_V <- Y_e_V(X.t0,de.diffusion,env)
 
 	mu <- funcmu(env=env)
-	aMat <- funca(env=env)   ## ¤³¤³¤Ç¥¨¥é¡¼ 2010/11/24, TBC
+	aMat <- funca(env=env)   ## 2010/11/24, TBC
 	Sigma <- funcsigma(env=env)
 
 	invSigma <- solve(Sigma)
Modified: pkg/yuima/R/asymptotic_term_third_function.R
===================================================================
--- pkg/yuima/R/asymptotic_term_third_function.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/asymptotic_term_third_function.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -8585,7 +8585,7 @@
 		    tmp[t] <- get_x_rho[,t] %*% tmpY[,j,t]
 		  }
 
-#‚Ç‚¿‚炪‚Í‚â‚¢‚©H
+#
 #		  for(i in 1:d.size){
 #		    tmp <- tmp + get_x_rho[i,] * tmpY[i,j,]
 #		  }

Modified: pkg/yuima/R/cogarchNoise.R
===================================================================
--- pkg/yuima/R/cogarchNoise.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/cogarchNoise.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -1,4 +1,4 @@
-# In this code we implement a filter that returns the increments of the undelying lévy process
+# In this code we implement a filter that returns the increments of the undelying levy process
 # if the model is a COGARCH(P,Q)
 # Using the squared of returns, we obtain the increment of Levy process using the relation
 # Y_t=e^{A\Delta t}Y_{t-\Delta t}+e^{A\left(\Delta t\right)}e\left(\Delta G_{t}\right)^{2}.

Modified: pkg/yuima/R/lse.R
===================================================================
--- pkg/yuima/R/lse.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/lse.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -90,7 +90,7 @@
 	mydots$lower <- unlist( lower[ nm[idx.diff] ])
 	
 	
-	if(length(start)>1){ #Â multidimensional optim				
+	if(length(start)>1){ #multidimensional optim				
 		oout <- do.call(optim, args=mydots)
 	} else { ### one dimensional optim
 		mydots$f <- mydots$fn

Modified: pkg/yuima/R/qgv.R
===================================================================
--- pkg/yuima/R/qgv.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/qgv.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -1,5 +1,5 @@
 ##:: function qgv
-##:: Estimating the local Hölder exponent of the path and the constant
+##:: Estimating the local Holder exponent of the path and the constant
 
 qgv<- function(yuima, filter.type="Daubechies", order=2, a=NULL){
 

Modified: pkg/yuima/R/simFunctional.R
===================================================================
--- pkg/yuima/R/simFunctional.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/simFunctional.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -80,7 +80,7 @@
   }
   
   resF <- funcF(yuima,X,e,expand.var=expand.var) #calculate F with X,e. size:vector[k.size]
-  resf <- funcf(yuima,X,e,expand.var=expand.var) #calculate f with X,e. size:array[k.size,division,r.size+1]  ## ¤¤¤Þ, ¤³¤³¤Ç¥¨¥é¡¼ 2010/11/13
+  resf <- funcf(yuima,X,e,expand.var=expand.var) #calculate f with X,e. size:array[k.size,division,r.size+1]  ## 2010/11/13
   Fe <- numeric(k.size)
   for(k in 1:k.size){
     Fe[k] <- sum(resf[k,1:division,]*dw)+resF[k]  #calculate Fe using resF and resf as (13.2).

Modified: pkg/yuima/R/yuima.model.R
===================================================================
--- pkg/yuima/R/yuima.model.R	2015-04-26 11:44:05 UTC (rev 377)
+++ pkg/yuima/R/yuima.model.R	2015-04-26 13:27:51 UTC (rev 378)
@@ -445,7 +445,7 @@
             expr <- expression(0)  # expr must have something
         }
         JUMP <- list(yuima.Simplifyobj(expr))
-    } else { # must be matrix, n.col = dimension of Lévy noise
+    } else { # must be matrix, n.col = dimension of Levy noise
         jump.coeff <- as.matrix(jump.coeff)
         c.j <- ncol(jump.coeff)
         r.j <- nrow(jump.coeff)