[Yuima-commits] r48 - in pkg/yuima: . R man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sun Dec 20 11:29:27 CET 2009
Author: iacus
Date: 2009-12-20 11:29:27 +0100 (Sun, 20 Dec 2009)
New Revision: 48
Modified:
pkg/yuima/DESCRIPTION
pkg/yuima/R/AllClasses.R
pkg/yuima/R/poisson.random.sampling.R
pkg/yuima/R/quasi-likelihood.R
pkg/yuima/R/sampling2grid.R
pkg/yuima/R/sim.euler.R
pkg/yuima/R/sim.euler.space.discretized.R
pkg/yuima/R/simulate.R
pkg/yuima/R/yuima.R
pkg/yuima/R/yuima.sampling.R
pkg/yuima/man/adaBayes.Rd
pkg/yuima/man/cce.Rd
pkg/yuima/man/limiting.gamma.Rd
pkg/yuima/man/model.parameter-class.Rd
pkg/yuima/man/poisson.random.sampling.Rd
pkg/yuima/man/quasi-likelihood.Rd
pkg/yuima/man/setData.Rd
pkg/yuima/man/setModel.Rd
pkg/yuima/man/setSampling.Rd
pkg/yuima/man/setYuima.Rd
pkg/yuima/man/simulate.Rd
pkg/yuima/man/yuima.data-class.Rd
pkg/yuima/man/yuima.sampling-class.Rd
Log:
small update to man pages and changed division with n
Modified: pkg/yuima/DESCRIPTION
===================================================================
--- pkg/yuima/DESCRIPTION 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/DESCRIPTION 2009-12-20 10:29:27 UTC (rev 48)
@@ -1,13 +1,12 @@
Package: yuima
Type: Package
Title: The YUIMA Project package
-Version: 0.0.78
-Date: 2009-12-18
+Version: 0.0.79
+Date: 2009-12-20
Depends: methods, zoo
Author: YUIMA Project Team.
Maintainer: Stefano M. Iacus <stefano.iacus at R-project.org>
-Description: The YUIMA Project for Simulation and Inference of
- Multidimensional Stochastic Differential Equations driven by
- with Abstract Noise.
+Description: The YUIMA Project for Simulation and Inference
+ for Stochastic Differential Equations.
License: GPL-2
URL: http://R-Forge.R-project.org/projects/yuima/
Modified: pkg/yuima/R/AllClasses.R
===================================================================
--- pkg/yuima/R/AllClasses.R 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/R/AllClasses.R 2009-12-20 10:29:27 UTC (rev 48)
@@ -54,7 +54,7 @@
setClass("yuima.sampling", representation(Initial = "numeric",
Terminal = "numeric",
- division = "numeric",
+ n = "numeric",
delta = "numeric",
grid = "numeric",
random = "ANY",
Modified: pkg/yuima/R/poisson.random.sampling.R
===================================================================
--- pkg/yuima/R/poisson.random.sampling.R 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/R/poisson.random.sampling.R 2009-12-20 10:29:27 UTC (rev 48)
@@ -32,7 +32,7 @@
}
## making time index
- # get rid of first element of X and elements that over division
+ # get rid of first element of X and elements that over n
# round Time to unit
xTime<-trunc(Time[0<Time & Num>Time])
# get rid of elements of value = 0
Modified: pkg/yuima/R/quasi-likelihood.R
===================================================================
--- pkg/yuima/R/quasi-likelihood.R 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/R/quasi-likelihood.R 2009-12-20 10:29:27 UTC (rev 48)
@@ -8,13 +8,13 @@
modelstate <- yuima at model@state.variable
modelpara <- yuima at model@parameter at drift
DRIFT <- yuima at model@drift
- division <- length(yuima)[1]
- drift <- matrix(0,division,d.size)
+ n <- length(yuima)[1]
+ drift <- matrix(0,n,d.size)
X <- as.matrix(onezoo(yuima))
for(i in 1:length(modelpara)){
assign(modelpara[i],para[i])
}
- for(t in 1:division){
+ for(t in 1:n){
Xt <- X[t,]
for(d in 1:d.size){
assign(modelstate[d],Xt[d])
@@ -35,14 +35,14 @@
modelstate <- yuima at model@state.variable
modelpara <- yuima at model@parameter at diffusion
DIFFUSION <- yuima at model@diffusion
- division <- length(yuima)[1]
- diff <- array(0, dim=c(d.size, r.size, division))
+ n <- length(yuima)[1]
+ diff <- array(0, dim=c(d.size, r.size, n))
X <- as.matrix(onezoo(yuima))
for(k in 1:length(modelpara)){
assign(modelpara[k], para[k])
}
for(r in 1:r.size){
- for(t in 1:division){
+ for(t in 1:n){
Xt <- X[t, ]
for(d in 1:d.size){
assign(modelstate[d], Xt[d])
@@ -58,9 +58,9 @@
##::calcurate diffusion%*%t(diffusion) matrix
calc.B <- function(diff){
d.size <- dim(diff)[1]
- division <- dim(diff)[3]
- B <- array(0, dim=c(d.size, d.size, division))
- for(t in 1:division){
+ n <- dim(diff)[3]
+ B <- array(0, dim=c(d.size, d.size, n))
+ for(t in 1:n){
B[, , t] <- diff[, , t]%*%t(diff[, , t])
}
return(B)
@@ -72,7 +72,7 @@
modelstate <- yuima at model@state.variable
modelpara <- yuima at model@parameter at diffusion
DIFFUSION <- yuima at model@diffusion
- division <- length(yuima)[1]
+ n <- length(yuima)[1]
X <- as.matrix(onezoo(yuima))
for(k in 1:length(modelpara)){
@@ -93,9 +93,9 @@
## }
## }
- B.grad <- array(0, dim=c(d.size, d.size, division, length(modelpara)))
+ B.grad <- array(0, dim=c(d.size, d.size, n, length(modelpara)))
for(k in 1:length(modelpara)){
- for(t in 1:division){
+ for(t in 1:n){
for(d in 1:d.size){
assign(modelstate[d], X[t, d])
}
@@ -193,12 +193,20 @@
}
d.size <- yuima at model@equation.number
- division <- length(yuima)[1]
+ n <- length(yuima)[1]
X <- as.matrix(onezoo(yuima))
- deltaX <- matrix(0, division-1, d.size)
- for(t in 1:(division-1)){
- deltaX[t, ] <- X[t+1, ]-X[t, ]
- }
+ deltaX <- matrix(0, n-1, d.size)
+ for(t in 1:(n-1))
+ deltaX[t, ] <- X[t+1, ]-X[t, ]
+
+#
+# print(system.time(for(t in 1:(n-1))
+# deltaX[t, ] <- X[t+1, ]-X[t, ]
+# ))
+# print(system.time(deltaX1 <- diff(X)))
+# print(deltaX)
+# print(deltaX1)
+
if(is.nan(theta2) || is.nan(theta1)){
stop("error: theta is not a namber in parameter matrix")
}
@@ -207,8 +215,8 @@
B <- calc.B(diff)
QL <- 0
- pn <- numeric(division-1)
- for(t in 1:(division-1)){
+ pn <- numeric(n-1)
+ for(t in 1:(n-1)){
if(det(as.matrix(B[, , t]))==0){
pn[t] <- log(1)
}else{
@@ -257,10 +265,10 @@
}
d.size <- yuima at model@equation.number
- division <- length(yuima)[1]
+ n <- length(yuima)[1]
X <- as.matrix(onezoo(yuima))
- deltaX <- matrix(0, division-1, d.size)
- for(t in 1:(division-1)){
+ deltaX <- matrix(0, n-1, d.size)
+ for(t in 1:(n-1)){
deltaX[t, ] <- X[t+1, ]-X[t, ]
}
if(is.nan(theta2) || is.nan(theta1)){
@@ -275,7 +283,7 @@
for(k in 1:length(QLG)){
pg1 <- 0
pg2 <- 0
- for(t in 1:(division-1)){
+ for(t in 1:(n-1)){
B.tmp <- as.matrix(B[, , t])
if(det(B.tmp)!=0){
B.grad.tmp <- as.matrix(B.grad[, , t, k])
@@ -413,10 +421,10 @@
}
d.size <- yuima at model@equation.number
- division <- length(yuima)[1]
+ n <- length(yuima)[1]
X <- as.matrix(onezoo(yuima))
- deltaX <- matrix(0, division-1, d.size)
- for(t in 1:(division-1)){
+ deltaX <- matrix(0, n-1, d.size)
+ for(t in 1:(n-1)){
deltaX[t, ] <- X[t+1, ]-X[t, ]
}
if(is.nan(theta2) || is.nan(theta1)){
@@ -431,8 +439,8 @@
pB <- calc.B(pdiff)
rQL <- 0
- pn <- numeric(division-1)
- for(t in 1:(division-1)){
+ pn <- numeric(n-1)
+ for(t in 1:(n-1)){
if(det(as.matrix(B[, , t]))*det(as.matrix(pB[, , t]))==0){
pn[t] <- log(1)
}else{
Modified: pkg/yuima/R/sampling2grid.R
===================================================================
--- pkg/yuima/R/sampling2grid.R 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/R/sampling2grid.R 2009-12-20 10:29:27 UTC (rev 48)
@@ -11,7 +11,7 @@
#Check if this grid is random
if (samp at random==FALSE){
#Regular deterministic grid
- return(seq(samp at Initial[1],samp at Terminal[1],length=samp at division[1]+1)) #Attention! do not treat multifrequency grid
+ return(seq(samp at Initial[1],samp at Terminal[1],length=samp at n[1]+1)) #Attention! do not treat multifrequency grid
}
return(1) #To do: Random grid
Modified: pkg/yuima/R/sim.euler.R
===================================================================
--- pkg/yuima/R/sim.euler.R 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/R/sim.euler.R 2009-12-20 10:29:27 UTC (rev 48)
@@ -10,12 +10,12 @@
r.size <- sdeModel at noise.number
d.size <- sdeModel at equation.number
Terminal <- yuima at sampling@Terminal[1]
- division <- yuima at sampling@division[1]
+ n <- yuima at sampling@n[1]
dX <- xinit
##:: set time step
- delta <- Terminal/division
+ delta <- Terminal/n
##:: check if DRIFT and/or DIFFUSION has values
has.drift <- sum(as.character(sdeModel at drift) != "(0)")
@@ -49,11 +49,11 @@
return(tmp)
}
- X_mat <- matrix(0, d.size, division+1)
+ X_mat <- matrix(0, d.size, n+1)
X_mat[,1] <- dX
if(has.drift){ ##:: consider drift term to be one of the diffusion term(dW=1)
- dW <- rbind( rep(1, division)*delta , dW)
+ dW <- rbind( rep(1, n)*delta , dW)
}
@@ -62,12 +62,12 @@
if(var.in.diff){ ##:: diffusions have state variables
##:: calcurate difference eq.
- for( i in 1:division){
+ for( i in 1:n){
dX <- dX + p.b(t=i*delta, X=dX) %*% dW[, i]
X_mat[,i+1] <- dX
}
}else{ ##:: diffusions have no state variables (not use p.b(). faster)
- sde.tics <- seq(0, Terminal, length=(division+1))
+ sde.tics <- seq(0, Terminal, length=(n+1))
sde.tics <- sde.tics[2:length(sde.tics)]
X_mat[, 1] <- dX
@@ -102,7 +102,7 @@
pbdata <- t(pbdata)
##:: calcurate difference eq.
- for( i in 1:division){
+ for( i in 1:n){
dX <- dX + pbdata[((i-1)*d.size+1):(i*d.size), ] %*% dW[, i]
X_mat[, i+1] <- dX
}
@@ -140,7 +140,7 @@
Uj <- sort( runif(N_sharp, 0, Terminal) )
ij <- NULL
for(i in 1:length(Uj)){
- Min <- min(which(c(1:division)*delta > Uj[i]))
+ Min <- min(which(c(1:n)*delta > Uj[i]))
ij <- c(ij, Min)
}
}
@@ -154,7 +154,7 @@
}
randJ <- eval(F) ## this expression is evaluated locally not in the yuimaEnv
j <- 1
- for(i in 1:division){
+ for(i in 1:n){
if(JAMP==FALSE || sum(i==ij)==0){
Pi <- 0
}else{
@@ -181,14 +181,14 @@
code <- suppressWarnings(sub("^(.+?)\\(.+", "\\1", sdeModel at measure$df$expr, perl=TRUE))
args <- unlist(strsplit(suppressWarnings(sub("^.+?\\((.+)\\)", "\\1", sdeModel at measure$df$expr, perl=TRUE)), ","))
dZ <- switch(code,
- rNIG=paste("rNIG(division, ", args[2], ", ", args[3], ", ", args[4], "*delta, ", args[5], "*delta)"),
- rIG=paste("rIG(division,", args[2], "*delta, ", args[3], ")"),
- rgamma=paste("rgamma(division, ", args[2], "*delta, ", args[3], ")"),
- rbgamma=paste("rbgamma(division, ", args[2], "*delta, ", args[3], ", ", args[4], "*delta, ", args[5], ")"),
-## rngamma=paste("rngamma(division, ", args[2], "*delta, ", args[3], ", ", args[4], ", ", args[5], "*delta, ", args[6], ")"),
- rngamma=paste("rngamma(division, ", args[2], "*delta, ", args[3], ", ", args[4], ", ", args[5], "*delta)"),
-## rstable=paste("rstable(division, ", args[2], ", ", args[3], ", ", args[4], ", ", args[5], ", ", args[6], ")")
- rstable=paste("rstable(division, ", args[2], ", ", args[3], ", ", args[4], "*delta^(1/",args[2],"), ", args[5], "*delta)")
+ rNIG=paste("rNIG(n, ", args[2], ", ", args[3], ", ", args[4], "*delta, ", args[5], "*delta)"),
+ rIG=paste("rIG(n,", args[2], "*delta, ", args[3], ")"),
+ rgamma=paste("rgamma(n, ", args[2], "*delta, ", args[3], ")"),
+ rbgamma=paste("rbgamma(n, ", args[2], "*delta, ", args[3], ", ", args[4], "*delta, ", args[5], ")"),
+## rngamma=paste("rngamma(n, ", args[2], "*delta, ", args[3], ", ", args[4], ", ", args[5], "*delta, ", args[6], ")"),
+ rngamma=paste("rngamma(n, ", args[2], "*delta, ", args[3], ", ", args[4], ", ", args[5], "*delta)"),
+## rstable=paste("rstable(n, ", args[2], ", ", args[3], ", ", args[4], ", ", args[5], ", ", args[6], ")")
+ rstable=paste("rstable(n, ", args[2], ", ", args[3], ", ", args[4], "*delta^(1/",args[2],"), ", args[5], "*delta)")
)
if(is.null(dZ)){ ##:: "otherwise"
@@ -198,7 +198,7 @@
dZ <- eval(parse(text=dZ))
##:: calcurate difference eq.
- for(i in 1:division){
+ for(i in 1:n){
assign(sdeModel at jump.variable, dZ[i], env)
if(sdeModel at J.flag){
Modified: pkg/yuima/R/sim.euler.space.discretized.R
===================================================================
--- pkg/yuima/R/sim.euler.space.discretized.R 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/R/sim.euler.space.discretized.R 2009-12-20 10:29:27 UTC (rev 48)
@@ -11,11 +11,11 @@
r.size <- sdeModel at noise.number
d.size <- sdeModel at equation.number
Terminal <- yuima at sampling@Terminal[1]
- division <- yuima at sampling@division[1]
+ n <- yuima at sampling@n[1]
dX <- xinit
##:: set time step
- delta <- Terminal/division
+ delta <- Terminal/n
@@ -54,7 +54,7 @@
appfunc <- suppressWarnings(approxfun(gg, xx))
##:: calculate inverse of G
- unif.a <- runif(division*2)
+ unif.a <- runif(n*2)
inv.a <- pmin(qnorm(1 - unif.a/4), appfunc(unif.a), na.rm=TRUE)
##:: make random time steps
Modified: pkg/yuima/R/simulate.R
===================================================================
--- pkg/yuima/R/simulate.R 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/R/simulate.R 2009-12-20 10:29:27 UTC (rev 48)
@@ -30,7 +30,7 @@
sdeModel <- yuima at model
Terminal <- yuima at sampling@Terminal[1]
- division <- yuima at sampling@division[1]
+ n <- yuima at sampling@n[1]
r.size <- sdeModel at noise.number
d.size <- sdeModel at equation.number
@@ -47,12 +47,8 @@
}
-
- ## str(sdeModel)
- ## print(Terminal)
- ## print(yuima at sampling@division)
- ## readline()
-
+
+
par.len <- length(sdeModel at parameter@all)
if(missing(true.parameter) & par.len>0){
@@ -91,8 +87,8 @@
}else if(dim(increment.W)[1] != r.size){
cat("\nLength of increment's row must be same as yuima at model@noise.number.\n")
return(NULL)
- }else if(dim(increment.W)[2] != division){
- cat("\nLength of increment's column must be same as yuima at sampling@division[1].\n")
+ }else if(dim(increment.W)[2] != n){
+ cat("\nLength of increment's column must be same as yuima at sampling@n[1].\n")
return(NULL)
}
}
@@ -105,8 +101,8 @@
}else if(dim(increment.L)[1] != r.size){
cat("\nLength of increment's row must be same as yuima at model@noise.number.\n")
return(NULL)
- }else if(dim(increment.L)[2] != division){
- cat("\nLength of increment's column must be same as yuima at sampling@division[1].\n")
+ }else if(dim(increment.L)[2] != n){
+ cat("\nLength of increment's column must be same as yuima at sampling@n[1].\n")
return(NULL)
}
}
@@ -123,7 +119,7 @@
##:: using Euler-Maruyama method
- delta <- Terminal/division
+ delta <- Terminal/n
@@ -139,9 +135,9 @@
}
} else {
- delta<-Terminal/division
- dW <- rnorm(division * r.size, 0, sqrt(delta))
- dW <- matrix(dW, ncol=division, nrow=r.size,byrow=TRUE)
+ delta<-Terminal/n
+ dW <- rnorm(n * r.size, 0, sqrt(delta))
+ dW <- matrix(dW, ncol=n, nrow=r.size,byrow=TRUE)
}
} else {
dW <- increment.W
Modified: pkg/yuima/R/yuima.R
===================================================================
--- pkg/yuima/R/yuima.R 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/R/yuima.R 2009-12-20 10:29:27 UTC (rev 48)
@@ -29,7 +29,7 @@
if(eqn!=length(sampling at Terminal)){
if(length(sampling at Terminal)==1){
sampling at Terminal <- rep(sampling at Terminal, eqn)
- sampling at division <- rep(sampling at division, eqn)
+ sampling at n <- rep(sampling at n, eqn)
}else{
cat("\nSampling's equation number missmatch.\n")
return(NULL)
Modified: pkg/yuima/R/yuima.sampling.R
===================================================================
--- pkg/yuima/R/yuima.sampling.R 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/R/yuima.sampling.R 2009-12-20 10:29:27 UTC (rev 48)
@@ -5,14 +5,14 @@
setMethod("initialize", "yuima.sampling",
- function(.Object, Initial, Terminal, division, delta, grid, random,
+ function(.Object, Initial, Terminal, n, delta, grid, random,
scale, regular){
.Object at scale <- 1
if(length(grid)>0){
testInitial<-(min(grid)==Initial)
testTerminal<-(max(grid)==Terminal)
- testdivision<-(abs(division-diff(range(grid))/mean(diff(grid))+1)<10^(-10))
+ testn<-(abs(n-diff(range(grid))/mean(diff(grid))+1)<10^(-10))
testdelta<-(abs(delta-mean(diff(grid)))<10^(-10))
testregular<-all(abs(diff(diff(grid)))<10^(-10))
@@ -22,18 +22,18 @@
if(!testTerminal){
cat("\n Terminal time has been set with the grid \n")
}
- if(!testdivision){
+ if(!testn){
cat("\n Division has been set with the grid \n")
}
if(!testdelta){
cat("\n delta has been set with the grid \n")
}
if(testregular){
- .Object at division <- diff(range(grid))/mean(diff(grid))+1
+ .Object at n <- diff(range(grid))/mean(diff(grid))+1
.Object at delta <- mean(diff(grid))
.Object at regular <- TRUE
}else{
- .Object at division <- length(grid)-1
+ .Object at n <- length(grid)-1
.Object at delta <- as.numeric(NULL)
.Object at regular <- FALSE
}
@@ -44,26 +44,26 @@
}else{
# There is no grid
eqn <- length(Terminal)
- if(length(Terminal)==length(division)){
+ if(length(Terminal)==length(n)){
.Object at Initial <- Initial
.Object at Terminal <- Terminal
- .Object at division <- division
+ .Object at n <- n
.Object at delta <- delta
.Object at grid <- grid
.Object at random <- random
.Object at regular <- regular
}else if(length(Terminal)==1){
.Object at Initial <- Initial
- .Object at Terminal <- rep(Terminal, length(division))
- .Object at division <- division
+ .Object at Terminal <- rep(Terminal, length(n))
+ .Object at n <- n
.Object at delta <- delta
.Object at grid <- grid
.Object at random <- random
.Object at regular <- regular
- }else if(length(division)==1){
+ }else if(length(n)==1){
.Object at Initial <- Initial
.Object at Terminal <- Terminal
- .Object at division <- rep(division, length(Terminal))
+ .Object at n <- rep(n, length(Terminal))
.Object at delta <- delta
.Object at grid <- grid
.Object at random <- random
@@ -75,72 +75,10 @@
return(.Object)
})
-setSampling <- function(Initial=0, Terminal=1, division=100, delta=0.1,
+setSampling <- function(Initial=0, Terminal=1, n=100, delta=0.1,
grid=as.numeric(NULL), random=FALSE, scale=1){
return(new("yuima.sampling", Initial=Initial, Terminal=Terminal,
- division=division, delta=delta, grid=grid, random=random,
+ n=n, delta=delta, grid=grid, random=random,
scale=scale, regular=TRUE))
}
-# accessors
-## setGeneric("setSampling",
-## function(x,Terminal,division)
-## standardGeneric("setSampling")
-## )
-
-## setMethod("setSampling", signature(x="yuima.model"),
-## function(x,Terminal=1,division=100){
-## if(length(x at equation.number) == 0) {
-## cat("model is empty!\n")
-## return(NULL)
-## }
-## d.size <- x at equation.number
-## if(length(Terminal)==1) {
-## Terminal <- rep(Terminal,d.size)
-## }
-## if(length(division)==1) {
-## division <- rep(division,d.size)
-## }
-## if(length(Terminal)!=d.size) {
-## cat("length of Terminal is not matched with model!\n")
-## return(NULL)
-## }
-## if(length(division)!=d.size) {
-## cat("length of division is not matched with model!\n")
-## return(NULL)
-## }
-## return(new("yuima.sampling", Terminal=Terminal, division=division ))
-## })
-
-## setMethod("setSampling", signature(x="yuima.data"),
-## function(x,Terminal=1,division=100){
-## d.size <- dim(get.zoo.data(x))[2]
-## if(is.null(d.size)) {
-## cat("data is empty!\n")
-## return(NULL)
-## }
-
-## if(length(Terminal)==1) {
-## Terminal <- rep(Terminal,d.size)
-## }
-## if(length(division)==1) {
-## division <- rep(division,d.size)
-## }
-## if(length(Terminal)!=d.size) {
-## cat("length of Terminal is not matched with model!\n")
-## return(NULL)
-## }
-## if(length(division)!=d.size) {
-## cat("length of division is not matched with model!\n")
-## return(NULL)
-## }
-## return(new("yuima.sampling", Terminal=Terminal, division=division ))
-## })
-
-## setMethod("setSampling", signature(x="yuima"),
-## function(x,Terminal=1,division=100){
-## if(length(x at model@EQNS) == 0) {
-## return(setSampling(x at data,Terminal,division))
-## }
-## return(setSampling(x at model,Terminal,division))
-## })
Modified: pkg/yuima/man/adaBayes.Rd
===================================================================
--- pkg/yuima/man/adaBayes.Rd 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/man/adaBayes.Rd 2009-12-20 10:29:27 UTC (rev 48)
@@ -29,9 +29,9 @@
set.seed(1)
diff.matrix <- matrix(c("theta1"),1,1)
mod <- setModel(drift=c("(-1)*theta2*x"),diffusion=diff.matrix,time.variable="t",state.variable="x")
- division <- 100
- Terminal <- (division)^(1/3)
- mod.sampling <- setSampling(Terminal=Terminal, division=division)
+ n <- 100
+ Terminal <- (n)^(1/3)
+ mod.sampling <- setSampling(Terminal=Terminal, n=n)
yuima.mod <- setYuima(model=mod, sampling=mod.sampling)
yuima.mod <- simulate(yuima.mod,
xinit=1,
@@ -56,13 +56,13 @@
QL <- 0
param <- numeric(2)
for( i in 1:5){
- PAR <- ml.ql(yuima.mod,theta2= rand[i,1],theta1=rand[i,2],h=(division^(-2/3)))
+ PAR <- ml.ql(yuima.mod,theta2= rand[i,1],theta1=rand[i,2],h=(n^(-2/3)))
if(PAR$value > QL){
QL <- PAR$value
param <- PAR$par
}
}
- BE <- adaBayes(yuima.mod,h=(division-1)^(-2/3),prior2=prior2,prior1=prior1,domain2=domain,domain1=domain,theta2.offset=param[1],theta1.offset=param[2])
+ BE <- adaBayes(yuima.mod,h=(n-1)^(-2/3),prior2=prior2,prior1=prior1,domain2=domain,domain1=domain,theta2.offset=param[1],theta1.offset=param[2])
print("True param")
print("theta2 = .6, theta1 = .3")
print("ML estimate")
Modified: pkg/yuima/man/cce.Rd
===================================================================
--- pkg/yuima/man/cce.Rd 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/man/cce.Rd 2009-12-20 10:29:27 UTC (rev 48)
@@ -11,12 +11,12 @@
cce(x)
}
\arguments{
- \item{x}{an object of class 'yuima' or 'yuima.data'}
+ \item{x}{an object of \code{\link{yuima-class}} or \code{\link{yuima.data-class}}.}
}
\details{
- This function is a method of class \code{\link{yuima.data-class}} and \code{\link{yuima-class}}.
+ This function is a method for objects of \code{\link{yuima.data-class}} and \code{\link{yuima-class}}.
It extracts the \code{data} slot when applied to a an object of
- class \code{\link{yuima-class}}.
+ \code{\link{yuima-class}}.
}
\value{
\item{value}{estimate of the covariance matrix}
@@ -46,7 +46,7 @@
set.seed(111)
## We use a function poisson.random.sampling to get observation by Poisson sampling.
-yuima.samp <- setSampling(Terminal = 1, division = 1200)
+yuima.samp <- setSampling(Terminal = 1, n = 1200)
yuima <- setYuima(model = cor.mod, sampling = yuima.samp)
yuima <- simulate(yuima)
psample<- poisson.random.sampling(yuima, rate = c(0.2,0.3), n = 1000)
Modified: pkg/yuima/man/limiting.gamma.Rd
===================================================================
--- pkg/yuima/man/limiting.gamma.Rd 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/man/limiting.gamma.Rd 2009-12-20 10:29:27 UTC (rev 48)
@@ -31,8 +31,8 @@
## Yuima
diff.matrix <- matrix(c("theta1"), 1, 1)
myModel <- setModel(drift=c("(-1)*theta2*x"), diffusion=diff.matrix, time.variable="t", state.variable="x")
-division <- 100
-mySampling <- setSampling(Terminal=(division)^(1/3), division=division)
+n <- 100
+mySampling <- setSampling(Terminal=(n)^(1/3), n=n)
myYuima <- setYuima(model=myModel, sampling=mySampling)
myYuima <- simulate(myYuima, xinit=1, true.parameter=c(0.6, 0.3))
Modified: pkg/yuima/man/model.parameter-class.Rd
===================================================================
--- pkg/yuima/man/model.parameter-class.Rd 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/man/model.parameter-class.Rd 2009-12-20 10:29:27 UTC (rev 48)
@@ -18,7 +18,7 @@
the Levy measure.}
\item{\code{all}:}{A vector of names of all the parameters found in the
components of the model.}
- \item{\code{common}:}{Vector of names of the parameters in common among
+ \item{\code{common}:}{A vector of names of the parameters in common among
drift, diffusion, jump and measure term.}
}
}
Modified: pkg/yuima/man/poisson.random.sampling.Rd
===================================================================
--- pkg/yuima/man/poisson.random.sampling.Rd 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/man/poisson.random.sampling.Rd 2009-12-20 10:29:27 UTC (rev 48)
@@ -7,7 +7,7 @@
poisson.random.sampling(x, rate, n)
}
\arguments{
- \item{x}{an object of class \code{\link{yuima.data-class}} or \code{\link{yuima-class}}.}
+ \item{x}{an object of \code{\link{yuima.data-class}} or \code{\link{yuima-class}}.}
\item{rate}{a Poisson intensity or a vector of Poisson intensities.}
\item{n}{a common multiplier to the Poisson intensities. The default value is 1.}
}
@@ -15,10 +15,10 @@
It returns an object
of type \code{\link{yuima.data-class}} which is a copy of the original input
data where observations are sampled according to
- the poisson process. The unsampled data are set to \code{NA}.
+ the Poisson process. The unsampled data are set to \code{NA}.
}
\value{
- an object of class \code{\link{yuima.data-class}}.
+ an object of \code{\link{yuima.data-class}}.
}
\author{The YUIMA Project Team}
\seealso{\link{cce}}
@@ -35,7 +35,7 @@
set.seed(111)
## We first simulate the two dimensional diffusion model
-yuima.samp <- setSampling(Terminal=1, division=1200)
+yuima.samp <- setSampling(Terminal=1, n=1200)
yuima <- setYuima(model=cor.mod, sampling=yuima.samp)
yuima.sim <- simulate(yuima)
Modified: pkg/yuima/man/quasi-likelihood.Rd
===================================================================
--- pkg/yuima/man/quasi-likelihood.Rd 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/man/quasi-likelihood.Rd 2009-12-20 10:29:27 UTC (rev 48)
@@ -45,22 +45,22 @@
#dXt^e = -theta2 * Xt^e * dt + theta1 * dWt
diff.matrix <- matrix(c("theta1"), 1, 1)
ymodel <- setModel(drift=c("(-1)*theta2*x"), diffusion=diff.matrix, time.variable="t", state.variable="x", solve.variable="x")
-division <- 100
+n <- 100
-ysamp <- setSampling(Terminal=(division)^(1/3), division=division)
+ysamp <- setSampling(Terminal=(n)^(1/3), n=n)
yuima <- setYuima(model=ymodel, sampling=ysamp)
set.seed(123)
yuima <- simulate(yuima, xinit=1, true.parameter=c(0.3, 0.1))
-QL <- ql(yuima, 0.8, 0.7, h=1/((division)^(2/3)))
+QL <- ql(yuima, 0.8, 0.7, h=1/((n)^(2/3)))
QL
## another way of parameter specification
##param <- list(theta2=0.8, theta1=0.7)
-##QL <- ql(yuima, h=1/((division)^(2/3)), param=param)
+##QL <- ql(yuima, h=1/((n)^(2/3)), param=param)
##QL
system.time(
-opt <- ml.ql(yuima, 0.8, 0.7, h=1/((division)^(2/3)), c(0, 1), c(0, 1))
+opt <- ml.ql(yuima, 0.8, 0.7, h=1/((n)^(2/3)), c(0, 1), c(0, 1))
)
print("True param")
print("theta2 = .3, theta1 = .1")
@@ -70,7 +70,7 @@
## another way of parameter specification
##interval <- list(theta2.lim=c(0,1), theta1.lim=c(0,1))
##system.time(
-##opt <- ml.ql(yuima, h=1/((division)^(2/3)), param=param, interval=interval)
+##opt <- ml.ql(yuima, h=1/((n)^(2/3)), param=param, interval=interval)
##)
##print("True param")
##print("theta2 = .3, theta1 = .1")
@@ -78,7 +78,7 @@
##opt$par
system.time(
-opt <- ml.ql(yuima, 0.8, 0.7, h=1/((division)^(2/3)), c(0, 1), c(0, 1), BFGS=TRUE)
+opt <- ml.ql(yuima, 0.8, 0.7, h=1/((n)^(2/3)), c(0, 1), c(0, 1), BFGS=TRUE)
)
print("True param")
print("theta2 = .3, theta1 = .1")
@@ -94,8 +94,8 @@
ymodel <- setModel(drift=drift.matrix, diffusion=diff.matrix, time.variable="t",
state.variable=c("x1", "x2"), solve.variable=c("x1", "x2"))
-division <- 100
-ysamp <- setSampling(Terminal=(division)^(1/3), division=division)
+n <- 100
+ysamp <- setSampling(Terminal=(n)^(1/3), n=n)
yuima <- setYuima(model=ymodel, sampling=ysamp)
set.seed(123)
@@ -104,12 +104,12 @@
theta2 <- c(0.8, 0.2) #c(theta2.1, theta2.2)
theta1 <- c(0.7, 0.1) #c(theta1.1, theta1.2)
-QL <- ql(yuima, theta2, theta1, h=1/((division)^(2/3)))
+QL <- ql(yuima, theta2, theta1, h=1/((n)^(2/3)))
QL
## another way of parameter specification
#param <- list(theta2=theta2, theta1=theta1)
-#QL <- ql(yuima, h=1/((division)^(2/3)), param=param)
+#QL <- ql(yuima, h=1/((n)^(2/3)), param=param)
#QL
theta2.1.lim <- c(0, 1)
@@ -120,19 +120,19 @@
theta1.lim <- t( matrix( c(theta1.1.lim, theta1.2.lim), 2, 2) )
system.time(
-opt <- ml.ql(yuima, theta2, theta1, h=1/((division)^(2/3)), theta2.lim, theta1.lim)
+opt <- ml.ql(yuima, theta2, theta1, h=1/((n)^(2/3)), theta2.lim, theta1.lim)
)
opt$par
## another way of parameter specification
#interval <- list(theta2.1.lim, theta2.2.lim, theta1.1.lim, theta1.2.lim)
#system.time(
-#opt <- ml.ql(yuima, h=1/((division)^(2/3)), param=param, interval=interval)
+#opt <- ml.ql(yuima, h=1/((n)^(2/3)), param=param, interval=interval)
#)
#opt$par
system.time(
-opt <- ml.ql(yuima, theta2, theta1, h=1/((division)^(2/3)), theta2.lim, theta1.lim, BFGS=TRUE)
+opt <- ml.ql(yuima, theta2, theta1, h=1/((n)^(2/3)), theta2.lim, theta1.lim, BFGS=TRUE)
)
opt$par
Modified: pkg/yuima/man/setData.Rd
===================================================================
--- pkg/yuima/man/setData.Rd 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/man/setData.Rd 2009-12-20 10:29:27 UTC (rev 48)
@@ -8,13 +8,13 @@
Set and access data of an object of type "yuima.data" or "yuima".
}
\description{
-\code{setData} constructs an object of class \code{\link{yuima.data-class}}.
+\code{setData} constructs an object of \code{\link{yuima.data-class}}.
\code{get.zoo.data} returns the content of the \code{zoo.data} slot of a
\code{\link{yuima.data-class}} object. (Note: value is a \code{list} of
\code{\link{zoo}} objects).
-\code{plot} plot method for object of class \code{\link{yuima.data-class}} or
+\code{plot} plot method for object of \code{\link{yuima.data-class}} or
\code{\link{yuima-class}}.
\code{dim} returns the \code{\link{dim}} of the \code{zoo.data} slot of a
@@ -35,29 +35,26 @@
\code{\link{yuima-class}}.}
}
\details{
-Objects in the \code{\link{yuima.data-class}} class contain two slots:
+Objects in the \code{\link{yuima.data-class}} contain two slots:
\describe{
\item{\code{original.data}:}{The slot \code{original.data} contains, as the
- name suggests, a copy of the original data passed by the user in the
- argument \code{original.data} of the function \code{setData}.
- It is intended for backup purposes.}
+ name suggests, a copy of the original data passed to the function
+ \code{setData}. It is intended for backup purposes.}
\item{\code{zoo.data}:}{the function \code{setData} tries to convert
\code{original.data} into an object of class \code{\link{zoo}}. The
- \code{\link{zoo}}-fied data are stored in the slot \code{zoo.data}.
-
+ coerced \code{\link{zoo}} data are stored in the slot \code{zoo.data}.
If the conversion fails the function exits with an error.
-
Internally, the \pkg{yuima} package stores and operates on
\code{\link{zoo}}-type objects.}
}
The function \code{get.zoo.data}
returns the content of the slot \code{zoo.data} of \code{x} if \code{x}
-is of class \code{\link{yuima.data-class}} or the content of
-\code{x at data@zoo.data} if \code{x} is of class \code{\link{yuima-class}}.
+is of \code{\link{yuima.data-class}} or the content of
+\code{x at data@zoo.data} if \code{x} is of \code{\link{yuima-class}}.
}
\value{
- \item{value}{a list of object(s) of class \code{\link{yuima.data-class}} for
+ \item{value}{a list of object(s) of \code{\link{yuima.data-class}} for
\code{setData}.
The content of the \code{zoo.data} slot for \code{get.zoo.data}}
}
Modified: pkg/yuima/man/setModel.Rd
===================================================================
--- pkg/yuima/man/setModel.Rd 2009-12-19 15:41:38 UTC (rev 47)
+++ pkg/yuima/man/setModel.Rd 2009-12-20 10:29:27 UTC (rev 48)
@@ -58,31 +58,28 @@
An object of \code{\link{yuima.model-class}} contains several slots:
\describe{
-\item{\code{drift}:}{is an \R expression which specifies the drift coefficient
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/yuima -r 48
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