[Robkalman-commits] r78 - in branches/robKalman_itwm/pkg/robKalman: R man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu May 15 16:06:06 CEST 2025
Author: ruckdeschel
Date: 2025-05-15 16:06:06 +0200 (Thu, 15 May 2025)
New Revision: 78
Added:
branches/robKalman_itwm/pkg/robKalman/R/diagnostics.R
branches/robKalman_itwm/pkg/robKalman/man/EStepShST.Rd
branches/robKalman_itwm/pkg/robKalman/man/initialization.Rd
Log:
itwm aufgeraumt
Added: branches/robKalman_itwm/pkg/robKalman/R/diagnostics.R
===================================================================
--- branches/robKalman_itwm/pkg/robKalman/R/diagnostics.R (rev 0)
+++ branches/robKalman_itwm/pkg/robKalman/R/diagnostics.R 2025-05-15 14:06:06 UTC (rev 78)
@@ -0,0 +1,80 @@
+
+### counting::::
+
+#%----------------------------------------------------------------------------
+# DarlehensCommitments.neu
+#%----------------------------------------------------------------------------
+
+nrow(DarlehensCommitments.neu)
+## completecases
+with(DarlehensCommitments.neu, idX <<- !is.na(Effective.date)&!is.na(Sector)&!is.na(COUNTRY)&!is.na(Currency)&!is.na(Laufzeit)&!is.na(Default.Spread))
+sum(idX)
+
+wL <- unlist(sapply(DarlehensCommitments.neu[,"COUNTRY"],function(x)which(x==LaenderTabelle[,"BlbDarlCom"])))
+wL.i <- unlist(sapply(DarlehensCommitments.neu[idX,"COUNTRY"],function(x)which(x==LaenderTabelle[,"BlbDarlCom"])))
+
+## Zahl der Fälle
+sum(LaenderTabelle[wL,"EmMarket"]==3, na.rm=T)
+sum(LaenderTabelle[wL.i,"EmMarket"]==3, na.rm=T)
+
+
+## Zahl der Laender
+
+sum(LaenderTabelle[unique(wL),"EmMarket"]==3, na.rm=T)
+sum(LaenderTabelle[unique(wL.i),"EmMarket"]==3, na.rm=T)
+
+sum(LaenderTabelle[unique(wL),"EmMarket"]<=3, na.rm=T)
+sum(LaenderTabelle[unique(wL.i),"EmMarket"]<=3, na.rm=T)
+
+#%----------------------------------------------------------------------------
+# DarlehensCommitments.neu
+#%----------------------------------------------------------------------------
+
+nrow(DarlehensCommitments.neu)
+## completecases
+with(DarlehensCommitments.neu, idX <<- !is.na(Effective.date)&!is.na(Sector)&!is.na(COUNTRY)&!is.na(Currency)&!is.na(Laufzeit)&!is.na(Default.Spread))
+sum(idX)
+
+wL <- unlist(sapply(DarlehensCommitments.neu[,"COUNTRY"],function(x)which(x==LaenderTabelle[,"BlbDarlCom"])))
+wL.i <- unlist(sapply(DarlehensCommitments.neu[idX,"COUNTRY"],function(x)which(x==LaenderTabelle[,"BlbDarlCom"])))
+
+## Zahl der Fälle
+sum(LaenderTabelle[wL,"EmMarket"]==3, na.rm=T)
+sum(LaenderTabelle[wL.i,"EmMarket"]==3, na.rm=T)
+
+
+## Zahl der Laender
+
+sum(LaenderTabelle[unique(wL),"EmMarket"]==3, na.rm=T)
+sum(LaenderTabelle[unique(wL.i),"EmMarket"]==3, na.rm=T)
+
+sum(LaenderTabelle[unique(wL),"EmMarket"]<=3, na.rm=T)
+sum(LaenderTabelle[unique(wL.i),"EmMarket"]<=3, na.rm=T)
+
+
+#%----------------------------------------------------------------------------
+# Issues
+#%----------------------------------------------------------------------------
+
+##
+nrow(Issues)
+
+## completecases
+with(Issues, idX1 <<- (!is.na(Announcement.date)&!is.na(Sector)&!is.na(Country)&!is.na(Curncy)&!is.na(Anlagefrist)&!is.na(Issuespread.o.Swp.)))
+sum(idX1)
+
+wL <- unlist(sapply(Issues[,"Country"],function(x)which(x==LaenderTabelle[,"BlbDarlCom"])))
+wL.i <- unlist(sapply(Issues[idX1,"Country"],function(x)which(x==LaenderTabelle[,"BlbDarlCom"])))
+
+## Zahl der Fälle
+sum(LaenderTabelle[wL,"EmMarket"]==3, na.rm=T)
+sum(LaenderTabelle[wL.i,"EmMarket"]==3, na.rm=T)
+
+
+## Zahl der Laender
+
+sum(LaenderTabelle[unique(wL),"EmMarket"]==3, na.rm=T)
+sum(LaenderTabelle[unique(wL.i),"EmMarket"]==3, na.rm=T)
+
+sum(LaenderTabelle[unique(wL),"EmMarket"]<=3, na.rm=T)
+sum(LaenderTabelle[unique(wL.i),"EmMarket"]<=3, na.rm=T)
Added: branches/robKalman_itwm/pkg/robKalman/man/EStepShST.Rd
===================================================================
--- branches/robKalman_itwm/pkg/robKalman/man/EStepShST.Rd (rev 0)
+++ branches/robKalman_itwm/pkg/robKalman/man/EStepShST.Rd 2025-05-15 14:06:06 UTC (rev 78)
@@ -0,0 +1,110 @@
+\name{MStep}
+\alias{MStep}
+\title{Implements the Maximization Step of the EM Algorithm.}
+\description{ This routine represents an implementation of the Maximization
+ part of the EM-Algorithm. It is based on the recursions provided in the references
+ mentioned below.
+
+}
+\usage{
+MStep(M,y,numobs,x,P,Pdep)
+}
+\arguments{
+ \item{M}{Observation matrix(Z in our notation): dimension q*q*n}
+ \item{y}{Observations: dimension q*n}
+ \item{x}{Smoothed values x_{t|n}, i.e for the estimated state at time t,
+ given observation until time n: dimension p*(n+1) ;
+ output of getSmoother()}
+ \item{P}{Smoothed values S_{t|n}, i.e for the estimated state at time t,
+ given observation until time n: dimension p*p*(n+1);
+ output of getSmoother()}
+ \item{Pdep}{Smoother covariances Cov(X_t,X_t-1|y_1:n): dimension p*p*n;
+ output of getSmoother()}
+
+}
+\value{
+ List of the components:
+ \item{F}{p*p observation matrix}
+ \item{Q}{p*p Covariance matrix corresponding to the noise of the states (x's) }
+ \item{V}{q*q Covariance matrix corresponding to the noise of the observations (y's)}
+
+}
+
+\references{
+ R. H. Shumway and D. S. Stoffer (1982): "An approach to time series smoothing
+ and forecasting using the EM algorithm". Journal of Time Series Analysis, vol. 3.
+
+ \url{http://www.stat.pitt.edu/stoffer/em.pdf}
+}
+
+\note{
+ See note on EM_Algo and proceed as indicated there. As in EM_Algo, loading
+ of all libraries and functions is required. This holds for the first example,
+ where the input of MStep depends on the output of the recFilter and of the results of
+ the smoothing recursions. For the second example, this is not necessary.
+
+}
+
+
+
+\author{Peter Ruckdeschel(Fraunhofer ITWM), Irina Ursachi (Fraunhofer ITWM)}
+\seealso{\code{\link{EM_Algo}}, \code{\link{initEMpseudo}},
+ \code{\link{recFilter}}, \code{\link{classKalman}}, \code{\link{getSmoother}}}
+\examples
+{
+ #runs <- 1
+ #M <- 20
+ T <- 100 ##number of observations
+ #eps <- 0.01
+ #itmax <- 30
+ #sn <- 0.5
+
+ pd <- 2
+ qd <- 3
+ F <- matrix(c(0.3,0.2,0.2,0.8),2,2)
+ Q <- MakePositive(matrix(c(3,1,1,2),2,2)*.1)
+ V <- MakePositive(matrix(c(3,1,1,1,2,0.3,1,.3,4),3,3)*.1)
+ Z <- matrix(c(3,-1,2,-1,1,1),3,2)
+ a <- c(0,0)
+ S <- Q
+
+ #Simulation of states and observations according to the state space model:
+ x <- simulateState(a=a, S=S, F=F, Qi=Q, Qc=Q, runs=runs, mc=c(0,0),tt=T)
+ y <- simulateObs(X=x,Z=Z,Vi=V,mc=numeric(qd),Vc=V,r=0,runs=runs)
+
+ ##Some noise-term introduction
+ resinitEM <- initEM.pseudo(F,Q,V, scalenoise=sn)
+ F0 <- resinitEM$F
+ Q0 <- resinitEM$Q
+ V0 <- resinitEM$V
+ Z1 <- array(Z, dim=c(qd,pd,T))
+ resEstep <- KalmanFilter(y, a, S, F0, Q0, Z1, V0, dropRuns = FALSE)
+ x0 <- resEstep$Xp
+ P1 <- resEstep$S1
+ P0 <- resEstep$S0
+ resSmoother <- getSmoother.Shumw.Stoff(y = y,
+ xf = resEstep$Xf,
+ S0 = resEstep$S0,
+ S1 = resEstep$S1,
+ KG = resEstep$KG[,,T], F=F0, Q=Q0, V=V0, Z=Z1)
+
+ ##In this following initialization, one can notice, how the M-Step of the EM algorithm
+ ##depends on the E-Step and smoothing recursions respectively:
+ resMStep <- MStep(M = Z1, y = matrix(y[,1,],qd,T),
+ x = matrix(resSmoother$xS[,1,],pd,T+1),
+ P = resSmoother$SS,
+ Pdep = resSmoother$SS1)
+}
+
+\examples{
+ ##This is NOT(!!) corresponding to the state space model
+ ##and is meant to give some insight in the computations and
+ ##matrix dimensions.
+ M <- array(rnorm(pd*qd*T, sd=1), dim=c(pd,qd,T));
+ y <- array(rnorm(qd*T,sd=0.8),dim=c(qd,T));
+ x <- array(rnorm(pd*(T+1),sd=0.9),dim=c(pd,(T+1)));
+ P <- array(rnorm(pd*pd*(T+1),sd=0.3),dim=c(pd,pd,(T+1)));
+ Pdep<- array(rnorm(pd*pd*T,sd=0.7),dim=c(pd,pd,T));
+ MStep(M,y,x,P,Pdep);
+
+}
\ No newline at end of file
Added: branches/robKalman_itwm/pkg/robKalman/man/initialization.Rd
===================================================================
--- branches/robKalman_itwm/pkg/robKalman/man/initialization.Rd (rev 0)
+++ branches/robKalman_itwm/pkg/robKalman/man/initialization.Rd 2025-05-15 14:06:06 UTC (rev 78)
@@ -0,0 +1,45 @@
+\name{initialization}
+\alias{init}
+\title{Provides an input possibility for the EM algorithm.}
+\description{
+ This routine simmulates the state space models. The output generated can be
+used as input for the EM algorithm.
+}
+
+\usage{
+ init(p,q,numobs)
+}
+
+\arguments{
+ \item{p}{}
+ \item{q}{length of the observations}
+ \item{numobs}{Number of observations, can also be refered to as
+ "number of time periods"}
+
+}
+
+\value{
+ List of the components:
+ \item{F}{p*p-dimensional observation matrix}
+ \item{Q}{p*p Covariance matrix corresponding to the noise of the states(x's)}
+ \item{V}{q*q Covariance matrix corresponding to the noise of the observations(y's)}
+ \item{Z}{q*p-dimensional design matrix}
+ \item{Y}{q*numobs dimensional observation matrix; each column corresponds
+ to the observations realized in one period}
+
+}
+
+\note{
+ This function is based on the SSM.R function in the RobKalman library. As
+mentioned before, this library can be found on r-forge.
+}
+
+\author{Peter Ruckdeschel, Irina Ursachi (Fraunhofer ITWM)}
+\seealso{\code{\link{SSM}}}
+\examples{
+ p<-2
+ q<-3
+ numobs<-4
+ init(p,q,numobs)
+
+}
\ No newline at end of file
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