[Robkalman-commits] r21 - in pkg/robKalman: . R
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Wed Mar 18 16:23:41 CET 2009
Author: ruckdeschel
Date: 2009-03-18 16:23:41 +0100 (Wed, 18 Mar 2009)
New Revision: 21
Removed:
pkg/robKalman/R/0AllClass.R
pkg/robKalman/R/ACMfilt.R
pkg/robKalman/R/ACMfilter.R
pkg/robKalman/R/AllGeneric.R
pkg/robKalman/R/AllGenerics.R
pkg/robKalman/R/AllInitialize.R
pkg/robKalman/R/AllPlot.R
pkg/robKalman/R/AllShow.R
pkg/robKalman/R/Control.R
pkg/robKalman/R/PosDefSymmMatrix.R
pkg/robKalman/R/Psi.R
pkg/robKalman/R/SSM.R
pkg/robKalman/R/Util.R
pkg/robKalman/R/arGM.R
pkg/robKalman/R/arGMinternal.R
pkg/robKalman/R/calibrateRLS.R
pkg/robKalman/R/classKalman.R
pkg/robKalman/R/generateSSMDistr.R
pkg/robKalman/R/mACMfilter.R
pkg/robKalman/R/mACMinternal.R
pkg/robKalman/R/rLSfilter.R
pkg/robKalman/R/recFilter-Methods.R
pkg/robKalman/R/recFilter.R
pkg/robKalman/R/simulateSScont.R
pkg/robKalman/R/solve.R
pkg/robKalman/R/tests.R
Modified:
pkg/robKalman/DESCRIPTION
Log:
had wrong r-versions in trunc folder...
deleting them (step 1)
Modified: pkg/robKalman/DESCRIPTION
===================================================================
--- pkg/robKalman/DESCRIPTION 2009-03-18 15:16:51 UTC (rev 20)
+++ pkg/robKalman/DESCRIPTION 2009-03-18 15:23:41 UTC (rev 21)
@@ -1,13 +1,13 @@
Package: robKalman
-Version: 0.2
-Date: 2007-07-03
+Version: 0.2.1
+Date: 2009-03-18
Title: Robust Kalman Filtering
Description: Routines for Robust Kalman Filtering --- the ACM- and rLS-filter
Author: Peter Ruckdeschel, Bernhard Spangl
-Maintainer: Peter Ruckdeschel <Peter.Ruckdeschel at uni-bayreuth.de>
+Maintainer: Peter Ruckdeschel <Peter.Ruckdeschel at itwm.fraunhofer.de>
Depends: R(>= 2.3.0), methods, graphics, startupmsg, dse1, dse2, MASS, limma, robustbase, numDeriv
Imports: stats, MASS
SaveImage: no
LazyLoad: yes
-License: GPL (version 2 or later)
-URL: http://www.uni-bayreuth.de/departments/math/org/mathe7/robKalman/
+License: LGPL-3
+URL: http://robkalman.r-forge.r-project.org/
Deleted: pkg/robKalman/R/0AllClass.R
===================================================================
--- pkg/robKalman/R/0AllClass.R 2009-03-18 15:16:51 UTC (rev 20)
+++ pkg/robKalman/R/0AllClass.R 2009-03-18 15:23:41 UTC (rev 21)
@@ -1,335 +0,0 @@
-################ general package preparation code, nothing to do with classes:
-
-.onLoad <- function(lib, pkg){
- require("methods", character = TRUE, quietly = TRUE)
-
-}
-
-
-.onAttach <- function(library, pkg)
-{
-buildStartupMessage(pkg="robKalman", library=library, packageHelp=TRUE #,
- #MANUAL=""
- )
- invisible()
-}
-
-#.onUnload <- function(libpath)
-#{
-# library.dynam.unload("distrEx", libpath)
-#}
-#
-
-
-################ Matrix class
-
-#### Code borrowed from package distrMod
-
-if (!(isClass("PosSemDefSymmMatrix")))
-setClass("PosSemDefSymmMatrix", contains = "matrix",
- prototype = prototype(matrix(1)),
- validity = function(object){
- if(nrow(object) != ncol(object))
- stop("no square matrix")
- if(any(!is.finite(object)))
- stop("inifinite or missing values in matrix")
- if(!isTRUE(all.equal(object, t(object), .Machine$double.eps^0.5)))
- stop("matrix is not symmetric")
- if(!all(eigen(object)$values > -100*.Machine$double.eps))
- stop("matrix is (numerically) not positive semi - definite")
- return(TRUE)
- })
-
-## positive definite, symmetric matrices with finite entries
-if (!(isClass("PosDefSymmMatrix")))
-setClass("PosDefSymmMatrix", contains = "PosSemDefSymmMatrix",
- validity = function(object){
- if(!all(eigen(object)$values > 100*.Machine$double.eps))
- stop("matrix is (numerically) not positive definite")
- valid <- getValidity(getClass("PosSemDefSymmMatrix"))
- valid(as(object, "PosSemDefSymmMatrix"))
- return(TRUE)
- })
-
-
-
-#
-## register zoo as "S4"-class
-setOldClass("zoo")
-#
-
-### infra-structure classes / class unions
-
-setClassUnion("IntegerOrNULL", c("integer", "NULL"))
-setClassUnion("ArrayOrNULL", c("array", "NULL"))
-setClassUnion("ArrayOrMatrix", c("array", "matrix"))
-setClassUnion("Hyperparamtype",
- c("NULL","ArrayOrMatrix", "OptionalFunction"))
-setClassUnion("sHyperparamtype",
- c("Hyperparamtype", "numeric"))
-setClassUnion("MatrixOrLogical", c("logical", "matrix"))
-
-
-###############################################################################
-#
-# State Space Model classes (SSMs)
-#
-###############################################################################
-
-
-# class SSM --- State space model
-setClass("SSM",
- representation = representation(
- name = "character", ## name of the ssm
- F = "Hyperparamtype", ## transition matrix/ces or NULL
- Z = "Hyperparamtype", ## observation matrix/ces or NULL
- Q = "Hyperparamtype", ## innovation covariance or NULL
- V = "Hyperparamtype", ## observation error covariance or NULL
- p = "numeric", ## state dimension
- q = "numeric", ## observation dimension
- a = "numeric", ## mean value of starting state
- S = "Hyperparamtype", ## variance of starting state
- time = "zoo"), ## time index
- prototype = prototype(name = gettext("a state space"),
- F = NULL,
- Z = NULL,
- Q = NULL,
- V = NULL,
- p = 1,
- q = 1,
- a = 0,
- S = NULL,
- time = zoo(1)),
- )
-
-# class TimeInvariantSSM
-setClass("TimeInvariantSSM",
- prototype = prototype(name = gettext("a time-invariant state space"),
- F = matrix(1),
- Z = matrix(1),
- Q = matrix(1),
- V = matrix(1),
- p = 1,
- q = 1,
- a = 0,
- S = matrix(1)),
- validity = function(object){
- if(!is.matrix(object at F)|!is.matrix(object at Z)|
- !is.matrix(object at Q)|!is.matrix(object at V)|
- !is.matrix(object at S))
- stop("Hyperparameters have to be matrices")
- return(TRUE)
- },
- contains = "SSM")
-
-###############################################################################
-#
-# Filter classes
-#
-###############################################################################
-
-setClass("recFilter", representation(name = "character",
- SSM = "SSM",
- Y = "array",
- X.filtered = "array",
- X.predicted = "array",
- Cov.filtered = "array",
- Cov.predicted = "array",
- Kalman.Gain = "array",
- time = "zoo"),
- prototype = prototype(name="classical Kalman Filter",
- SSM = new("TimeInvariantSSM"),
- Y = array(1,dim=c(1,1,1)),
- X.filtered = array(1,dim=c(1,1,1)),
- X.predicted = array(1,dim=c(1,1,1)),
- Cov.filtered = array(1,dim = c(1,1,1)),
- Cov.predicted = array(1,dim = c(1,1,1)),
- Kalman.Gain = array(1,dim = c(1,1,1)),
- time = zoo(1))
-
- )
-
-
-setClass("robrecFilter", representation(
- name.rob = "character",
- X.rob.filtered = "array",
- X.rob.predicted = "array",
- Cov.rob.filtered = "array",
- Cov.rob.predicted = "array",
- Kalman.rob.Gain = "array",
- IndIO = "MatrixOrLogical",
- IndAO = "MatrixOrLogical",
- rob.correction.ctrl = "list",
- rob.prediction.ctrl = "list",
- nsim = "numeric",
- RNGstate = "IntegerOrNULL",
- Cov.rob.filtered.sim = "ArrayOrNULL",
- Cov.rob.predicted.sim = "ArrayOrNULL"
- ),
- prototype = prototype(
- name="rLS Filter",
- X.rob.filtered = array(1,dim=c(1,1,1)),
- X.rob.predicted = array(1,dim=c(1,1,1)),
- Cov.rob.filtered = array(1,dim = c(1,1,1)),
- Cov.rob.predicted = array(1,dim = c(1,1,1)),
- Kalman.rob.Gain = array(1,dim = c(1,1,1)),
- IndIO = FALSE,
- IndAO = FALSE,
- nsim = 0,
- RNGstate = as.integer(0),
- rob.correction.ctrl = list(NULL),
- rob.prediction.ctrl = list(NULL),
- Cov.rob.filtered.sim = array(1,dim = c(1,1,1)),
- Cov.rob.predicted.sim = array(1,dim = c(1,1,1))),
- contains = "recFilter")
-
-###############################################################################
-#
-# Control classes
-#
-###############################################################################
-#setClass("ACMcontrol",representation())
-#setClass("rLScontrol",representation())
-
-
-setClass("RecFiltControl", representation(
- name = "character",
- init = "function",
- predict = "function",
- correct = "function"),
- contains = "VIRTUAL")
-
-setClass("KalmanControl",
- prototype = prototype(
- name = "classical Kalman Filter",
- init = .cKinitstep,
- predict = .cKpredstep,
- correct = .cKcorrstep),
- contains="RecFiltControl"
- )
-
-setClass("robrecControl", representation(
- controls = "list",
- name.rob = "character",
- init.rob = "function",
- predict.rob = "function",
- correct.rob = "function"),
- prototype = prototype(
- name.rob = "rLS Filter",
- init.rob = .cKinitstep,
- predict.rob = .cKpredstep,
- correct.rob = .rLScorrstep,
- controls = list(b = 2, norm = EuclideanNorm)
- ),
- contains="RecFiltControl"
- )
-# = paste(gettext(
-# "Control set and init, prediction and"
-# ),gettext(
-# "correction step for the classical Kalman Filter\n"
-# ),gettext(
-# "and the rLS Filter"
-# )),
-
-###############################################################################
-#
-# multivariate Distribution classes
-#
-###############################################################################
-
-setClass("SSMDistribution.f", representation(
- r.init = "function",
- r.innov = "function",
- r.obs = "function"),
- prototype = prototype(r.init = mvrnorm,
- r.innov = mvrnorm,
- r.obs = mvrnorm))
-
-setClass("SSMellDistribution.f", representation(
- m.init = "sHyperparamtype",
- S.init = "Hyperparamtype",
- m.innov = "sHyperparamtype",
- S.innov = "Hyperparamtype",
- m.obs = "sHyperparamtype",
- S.obs = "Hyperparamtype"),
- prototype = prototype(m.init = 0, S.init = matrix(1),
- m.innov = 0, S.innov = matrix(1),
- m.obs = 0, S.obs = matrix(1)),
- contains = "SSMDistribution.f")
-
-setClass("SSMConvDistribution.f", representation(
- ideal = "SSMDistribution.f",
- cont = "SSMellDistribution.f",
- r.IO = "numeric",
- r.AO = "numeric"),
- prototype = prototype(ideal = new("SSMellDistribution.f"),
- cont = new("SSMellDistribution.f"),
- r.IO = 0, r.AO = 0),
- validity = function(object){
- if (object at r.IO<0||object at r.AO<0||object at r.IO>1||object at r.AO>1)
- stop("Radii must be between 0 and 1")
- return(TRUE)})
-
-
-###############################################################################
-#
-# SSM + Distribution classes
-#
-###############################################################################
-setClass("SSMwithDistribution", representation(
- SSM = "SSM",
- Distribution = "SSMDistribution.f"),
- prototype = prototype(SSM = new("SSM"),
- Distribution = SSMDistribution.f(new("SSM"))))
-setClass("SSMwithConvDistribution", representation(
- SSM = "SSM",
- Distribution = "SSMConvDistribution.f"),
- prototype = prototype(SSM = new("SSM"),
- Distribution = SSMContDistribution.f(new("SSM"))))
-
-setClassUnion("SSMDistr", c("SSMDistribution.f",
- "SSMConvDistribution.f"))
-
-###############################################################################
-#
-# SSM - Simulation classes
-#
-###############################################################################
-setClass("SSMsimulation", representation(
- SSM = "SSM",
- Distr = "SSMDistr",
- RNGstate = "numeric",
- states = "ArrayOrMatrix",
- obs = "ArrayOrMatrix"),
- prototype = prototype(SSM = new("SSM"),
- Distr = new("SSMDistribution.f"),
- RNGstate = structure(1, kind = as.list(RNGkind())),
- states = matrix(1), obs = matrix(1)))
-
-setClass("SSMcontSimulation", representation(
- states.id = "ArrayOrMatrix",
- obs.id = "ArrayOrMatrix",
- Ind.IO = "MatrixOrLogical",
- Ind.AO = "MatrixOrLogical"
- ),
- prototype = prototype(
- Distr = new("SSMConvDistribution.f"),
- states.id = matrix(1), obs.id = matrix(1),
- Ind.IO = FALSE, Ind.AO = FALSE
- ),
- validity = function(object){
- fct <- function(m){
- mt <- paste(deparse(substitute(m)),sep="",collapse="")
- if(is.matrix(m)){
- if(!all(is.logical(m)))
- stop(gettextf("Matrix %s has to have logical entries.", mt))
- return(TRUE)
- }
- else return(TRUE)
- }
- return(fct(object at Ind.IO)&&fct(object at Ind.AO))
- },
- contains = "SSMsimulation")
-
-
-
\ No newline at end of file
Deleted: pkg/robKalman/R/ACMfilt.R
===================================================================
--- pkg/robKalman/R/ACMfilt.R 2009-03-18 15:16:51 UTC (rev 20)
+++ pkg/robKalman/R/ACMfilt.R 2009-03-18 15:23:41 UTC (rev 21)
@@ -1,85 +0,0 @@
-ACMfilt <- function (x, gm, s0=0,
- psi="Hampel", a=2.5, b=a, c=5.0,
- flag="weights", lagsmo=TRUE)
-{
-###########################################
-##
-## R-function: ACMfilt - approximate conditional-mean filtering (wrapper)
-## author: Bernhard Spangl
-## version: 1.1 (2007-08-13 and 2006-08-31)
-## References:
-## [Mart79c] R.D. Martin, Approximate Conditional-mean Type Smoothers
-## and Interpolators (1979)
-## [Mart81b] R.D. Martin, Robust Methods for Time Series (1981)
-## [MarT82b] R.D. Martin & D.J. Thomson, Robust-resistent Spectrum
-## Estimation (1982)
-##
-###########################################
-
-## Paramters:
-## x ... univariate time series (vector)
-## gm ... list as produced by function 'arGM' which includes components
-## 'ar' containing the AR(p) coefficient estimates, 'sinnov' containing
-## innovation scale estiamtes from AR(p) fits of orders 1 through p;
-## 'Cx' containing an estimate of the p by p autocovariance matrix,
-## and 'mu', the estimated mean of 'x'.
-## s0 ... scale of nominal Gaussian component of the additive noise
-## psi ... influence function to be used (default: "Hampel",
-## only Hampel's psi function available at the moment)
-## a, b, c ... tuning constants for Hampel's psi-function
-## (defaul: a=b=2.5, c=5.0)
-## flag ... character, if "weights" (default), use psi(t)/t to calculate
-## the weights; if "deriv", use psi'(t)
-## lagsmo ... logical, if TRUE (default) lag p-1 smoothing is performed;
-## if FALSE filtering from the top of ^X_t is performed
-
-## Variable definitions:
-
- N <- length(x)
- phi <- gm$ar
- p <- length(phi)
- si <- gm$sinnov[p]
- Cx <- gm$Cx
- Phi <- cbind(rbind(phi[-p], diag(rep(1, (p-1)))), c(phi[p], rep(0, (p-1))))
- Q <- matrix(0, p, p)
-## Q <- diag(rep(0, p))
- Q[1, 1] <- si^2
-
- m0 <- rep(0, p)
- H <- matrix(c(1, rep(0, (p-1))), 1, p)
- V <- matrix(s0^2)
- psi <- .psi(psi)
-
- ## Centering:
- x <- x - gm$mu
- ACMres <- ACMfilter(Y = matrix(x,1,N), a = m0, S = Cx, F = Phi,
- Q = Q, Z = H, V = V,
- s0 = s0, psi = psi, apsi = a, bpsi = b, cpsi = c,
- flag = flag)
-
- ### from version ... the return value $X[r]f is of
- # dimension p x runs x (N+1)
- # => have to cast it back to dimension p x (N+1)
-
- X.ck <- matrix(ACMres$Xf[,1,], p, N+1); X.ck <- X.ck[,2:(N+1)]
- X <- matrix(ACMres$Xrf[,1,], p, N+1); X <- X[,2:(N+1)]
- st <- as.numeric(unlist(ACMres$rob1L))
-
-
- if (!lagsmo) {
- x.ck <- X.ck[1, ]
- x <- X[1, ]
- } else {
- x.ck <- c(X.ck[p, p:N], X.ck[(p-1):1, N])
- x <- c(X[p, p:N], X[(p-1):1, N])
- }
-
-## ARmodel <- .ARmodel(x, p)
-## y <- ARmodel$y
-## Z <- ARmodel$Z
-## r <- resid(lm.fit(Z, y))
-
- return(list(filt.ck=x.ck +gm$mu, filt=x + gm$mu, st=st)) #,
-## r=c(rep(NA, p), r)))
-
-}
Deleted: pkg/robKalman/R/ACMfilter.R
===================================================================
--- pkg/robKalman/R/ACMfilter.R 2009-03-18 15:16:51 UTC (rev 20)
+++ pkg/robKalman/R/ACMfilter.R 2009-03-18 15:23:41 UTC (rev 21)
@@ -1,97 +0,0 @@
-.getcorrCovACM <- function (S1, K, Z, W=diag(nrow(Z)))
-{
-###########################################
-##
-## R-function: .corrCov - computes filtering error covarince matrix
-## (internal function)
-## author: Bernhard Spangl
-## version: 1.0 (2006-05-22)
-##
-###########################################
-
-## Paramters:
-## S1 ... prediction error covariance matrix
-## K ... Kalman gain
-## W ... weight matrix
-## Z ... observation matrix
-
- S1 - K %*% W %*% Z %*% S1
-}
-
-##steps for classical Kalman filter (cK)
-.ACMinitstep <- function(a, S, i, ...)
- {dots <- list(...)
- if(hasArg("s0"))
- s0 <- dots$"s0"
- else
- s0 <- NULL
- list( x0 = a, S0 = S, s0 = s0)}
-
-
-.ACMpredstep <- function (x0, S0, F, Q, i, rob0, s0, ...) ### S=P F= Phi
-{
-###########################################
-##
-## R-function: .ACMpredstep - prediction step (internal function)
-## author: Bernhard Spangl
-## version: 1.0 (2006-05-22)
-##
-###########################################
-
-## Paramters:
-## x0 ... state vector (filter estimate)
-## F=Phi ... design matrix of state equation
-## S0 ... filtering error covariance matrix
-## Q ... covariance matrix of state innovation process
-## rob0 ... general robust parameter --- here: scale s0 of nominal Gaussain component of additive noise
- S1 <- .getpredCov(S0, F, Q)
- return(list(x1 = F %*% x0, S1 = S1, rob1 = sqrt(S1[1, 1] + s0), Ind = FALSE))
-}
-
-.ACMcorrstep <- function (y, x1, S1, Z, V, i, rob1, dum = NULL,
- psi, apsi, bpsi, cpsi, flag, ...)
-{
-###########################################
-##
-## R-function: .ACMcorrstep - correction step (internal function)
-## author: Bernhard Spangl
-## version: 1.0 (2006-05-22)
-##
-###########################################
-
-## Paramters:
-## y ... univariate time series
-## x1 ... state vector (one-step-ahead predictor)
-## rob1 ... general robust parameter --- here st ... time-dependent scale parameter
-## S1 ... prediction error covariance matrix
-## Z ... observation matrix
-## dum ... dummy variable for compatibility with ... argument of calling function
-## V ... covariance matrix of observation noise
-## psi ... influence function to be used
-## apsi, bpsi, cpsi ... tuning constants for Hampel's psi-function
-## (default: apsi=bpsi=2.5, cpsi=5.0)
-## flag ... character, if "weights" (default), use psi(t)/t to calculate
-## the weights; if "deriv", use psi'(t)
-
- # to be compatible with parallel computing of a bunch of time series
- y <- y[,1]
- x1 <- x1[,1]
-
- st <- rob1
-
- K <- .getKG(S1, Z, V)
-
- rst <- (y - x1[1])/st
-
- ps <- psi(rst, apsi, bpsi, cpsi)
- dx <- K * st * ps
- x0 <- x1 + dx
-
- ind <- (abs(rst-ps)>10^-8)
-
- w <- psi(rst, apsi, bpsi, cpsi, flag)
-
- S0 <- .getcorrCovACM(S1, K, Z, W = w*diag(rep(1, nrow(Z))))
-
- return(list(x0 = x0, K = K, S0 = S0, Ind = ind, rob0 = rob1))
-}
Deleted: pkg/robKalman/R/AllGeneric.R
===================================================================
--- pkg/robKalman/R/AllGeneric.R 2009-03-18 15:16:51 UTC (rev 20)
+++ pkg/robKalman/R/AllGeneric.R 2009-03-18 15:23:41 UTC (rev 21)
@@ -1,10 +0,0 @@
-#if(!isGeneric("type")){
-# setGeneric("type", function(object) standardGeneric("type"))
-#}
-#if(!isGeneric("center")){
-# setGeneric("center", function(object) standardGeneric("center"))
-#}
-#if(!isGeneric("center<-")){
-# setGeneric("center<-", function(object, value) standardGeneric("center<-"))
-#}
-#
Deleted: pkg/robKalman/R/AllGenerics.R
===================================================================
--- pkg/robKalman/R/AllGenerics.R 2009-03-18 15:16:51 UTC (rev 20)
+++ pkg/robKalman/R/AllGenerics.R 2009-03-18 15:23:41 UTC (rev 21)
@@ -1,123 +0,0 @@
-if(!isGeneric("solve")){
- setGeneric("solve", function(a,b,...) standardGeneric("solve"))
-}
-############################################################################
-# Access methods
-############################################################################
-
-if(!isGeneric("name"))
- setGeneric("name", function(object) standardGeneric("name"))
-
-if(!isGeneric("getp"))
- setGeneric("getp", function(object) standardGeneric("getp"))
-if(!isGeneric("getq"))
- setGeneric("getq", function(object) standardGeneric("getq"))
-
-if(!isGeneric("getF"))
- setGeneric("getF", function(object) standardGeneric("getF"))
-if(!isGeneric("getZ"))
- setGeneric("getZ", function(object) standardGeneric("getZ"))
-if(!isGeneric("getQ"))
- setGeneric("getQ", function(object) standardGeneric("getQ"))
-if(!isGeneric("getV"))
- setGeneric("getV", function(object) standardGeneric("getV"))
-if(!isGeneric("geta"))
- setGeneric("geta", function(object) standardGeneric("geta"))
-if(!isGeneric("getS"))
- setGeneric("getS", function(object) standardGeneric("getS"))
-if(!isGeneric("time"))
- setGeneric("time", function(x,...) standardGeneric("time"))
-
-if(!isGeneric("SSM"))
- setGeneric("SSM", function(object, ...) standardGeneric("SSM"))
-if(!isGeneric("Y"))
- setGeneric("Y", function(object, ...) standardGeneric("Y"))
-if(!isGeneric("X.filtered"))
- setGeneric("X.filtered", function(object, ...) standardGeneric("X.filtered"))
-if(!isGeneric("X.predicted"))
- setGeneric("X.predicted", function(object, ...) standardGeneric("X.predicted"))
-if(!isGeneric("Cov.filtered"))
- setGeneric("Cov.filtered", function(object, ...) standardGeneric("Cov.filtered"))
-if(!isGeneric("Cov.predicted"))
- setGeneric("Cov.predicted", function(object, ...) standardGeneric("Cov.predicted"))
-if(!isGeneric("Kalman.Gain"))
- setGeneric("Kalman.Gain", function(object, ...) standardGeneric("Kalman.Gain"))
-if(!isGeneric("X.rob.filtered"))
- setGeneric("X.rob.filtered", function(object, ...) standardGeneric("X.rob.filtered"))
-if(!isGeneric("X.rob.predicted"))
- setGeneric("X.rob.predicted", function(object, ...) standardGeneric("X.rob.predicted"))
-if(!isGeneric("Cov.rob.filtered"))
- setGeneric("Cov.rob.filtered", function(object, ...) standardGeneric("Cov.rob.filtered"))
-if(!isGeneric("Cov.rob.predicted"))
- setGeneric("Cov.rob.predicted", function(object, ...) standardGeneric("Cov.rob.predicted"))
-if(!isGeneric("Kalman.rob.Gain"))
- setGeneric("Kalman.rob.Gain", function(object, ...) standardGeneric("Kalman.rob.Gain"))
-if(!isGeneric("rob.correction.ctrl"))
- setGeneric("rob.correction.ctrl", function(object, ...) standardGeneric("rob.correction.ctrl"))
-if(!isGeneric("rob.prediction.ctrl"))
- setGeneric("rob.prediction.ctrl", function(object, ...) standardGeneric("rob.prediction.ctrl"))
-if(!isGeneric("IndIO"))
- setGeneric("IndIO", function(object, ...) standardGeneric("IndIO"))
-if(!isGeneric("IndAO"))
- setGeneric("IndAO", function(object, ...) standardGeneric("IndAO"))
-if(!isGeneric("nsim"))
- setGeneric("nsim", function(object, ...) standardGeneric("nsim"))
-if(!isGeneric("RNGstate"))
- setGeneric("RNGstate", function(object, ...) standardGeneric("RNGstate"))
-if(!isGeneric("Cov.rob.filtered.sim"))
- setGeneric("Cov.rob.filtered.sim", function(object, ...) standardGeneric("Cov.rob.filtered.sim"))
-if(!isGeneric("Cov.rob.predicted.sim"))
- setGeneric("Cov.rob.predicted.sim", function(object, ...) standardGeneric("Cov.rob.predicted.sim"))
-if(!isGeneric("init"))
- setGeneric("init", function(object, ...) standardGeneric("init"))
-if(!isGeneric("predict"))
- setGeneric("predict", function(object, ...) standardGeneric("predict"))
-if(!isGeneric("correct"))
- setGeneric("correct", function(object, ...) standardGeneric("correct"))
-if(!isGeneric("init.rob"))
- setGeneric("init.rob", function(object, ...) standardGeneric("init.rob"))
-if(!isGeneric("name.rob"))
- setGeneric("name.rob", function(object, ...) standardGeneric("name.rob"))
-if(!isGeneric("predict.rob"))
- setGeneric("predict.rob", function(object, ...) standardGeneric("predict.rob"))
-if(!isGeneric("correct.rob"))
- setGeneric("correct.rob", function(object, ...) standardGeneric("correct.rob"))
-if(!isGeneric("controls"))
- setGeneric("controls", function(object, ...) standardGeneric("controls"))
-
-############################################################################
-# Replacement methods
-############################################################################
-
-if(!isGeneric("name<-"))
- setGeneric("name<-",
- function(object, value) standardGeneric("name<-"))
-
-if(!isGeneric("setp<-"))
- setGeneric("setp<-", function(object, value) standardGeneric("setp<-"))
-if(!isGeneric("setq<-"))
- setGeneric("setq<-", function(object, value) standardGeneric("setq<-"))
-
-if(!isGeneric("setF<-"))
- setGeneric("setF<-", function(object, value) standardGeneric("setF<-"))
-if(!isGeneric("setZ<-"))
- setGeneric("setZ<-", function(object, value) standardGeneric("setZ<-"))
-if(!isGeneric("setQ<-"))
- setGeneric("setQ<-", function(object, value) standardGeneric("setQ<-"))
-if(!isGeneric("setV<-"))
- setGeneric("setV<-", function(object, value) standardGeneric("setV<-"))
-if(!isGeneric("seta<-"))
- setGeneric("seta<-", function(object, value) standardGeneric("seta<-"))
-if(!isGeneric("setS<-"))
- setGeneric("setS<-", function(object, value) standardGeneric("setS<-"))
-if(!isGeneric("time<-"))
- setGeneric("time<-", function(x, value) standardGeneric("time<-"))
-
-if(!isGeneric(".make.project"))
-setGeneric(".make.project",function(object, ...) standardGeneric(".make.project"))
-
-if(!isGeneric("kalman"))
-setGeneric("kalman",function(smooth, ...) standardGeneric("kalman"))
-
-if(!isGeneric("kalmanRob"))
-setGeneric("kalmanRob",function(method, smooth, ...) standardGeneric("kalmanRob"))
Deleted: pkg/robKalman/R/AllInitialize.R
===================================================================
--- pkg/robKalman/R/AllInitialize.R 2009-03-18 15:16:51 UTC (rev 20)
+++ pkg/robKalman/R/AllInitialize.R 2009-03-18 15:23:41 UTC (rev 21)
@@ -1,3 +0,0 @@
-#### as to whether to use Generating functions or to use initialize methods:
-#### http://tolstoy.newcastle.edu.au/R/e2/devel/07/01/1976.html
-
Deleted: pkg/robKalman/R/AllPlot.R
===================================================================
--- pkg/robKalman/R/AllPlot.R 2009-03-18 15:16:51 UTC (rev 20)
+++ pkg/robKalman/R/AllPlot.R 2009-03-18 15:23:41 UTC (rev 21)
@@ -1,7 +0,0 @@
-#setMethod("plot", "ParamFamily",
-# function(x,y=NULL,...){
-# e1 <- x at distribution
-# if(!is(e1, "UnivariateDistribution")) stop("not yet implemented")
-#
-# plot(e1)
-# })
Deleted: pkg/robKalman/R/AllShow.R
===================================================================
--- pkg/robKalman/R/AllShow.R 2009-03-18 15:16:51 UTC (rev 20)
+++ pkg/robKalman/R/AllShow.R 2009-03-18 15:23:41 UTC (rev 21)
@@ -1,161 +0,0 @@
-#setMethod("show", "ParamFamParameter",
-# function(object){
-# cat(paste("An object of class", dQuote(class(object)), "\n"))
-# cat("name:\t", object at name, "\n")
-# cat("main:\t", object at main, "\n")
-# if(!is.null(object at nuisance))
-# cat("nuisance:\t", object at nuisance, "\n")
-# if(!identical(all.equal(object at trafo, diag(length(object)),
-# tolerance = .Machine$double.eps^0.5), TRUE)){
-# cat("trafo:\n")
-# print(object at trafo)
-# }
-# })
-#setMethod("show", "Symmetry",
-# function(object){
-# cat("type of symmetry:\t", object at type, "\n")
-# if(!is.null(object at SymmCenter))
-# cat("center of symmetry:\n")
-# print(object at SymmCenter)
-# })
-#setMethod("show", "ParamFamily",
-# function(object){
-# cat(paste("An object of class", dQuote(class(object)), "\n"))
-# cat("### name:\t", object at name, "\n")
-# cat("\n### distribution:\t")
-# print(object at distribution)
-# cat("\n### param:\t")
-# show(object at param)
-# if(length(object at props) != 0){
-# cat("\n### props:\n")
-# show(object at props)
-# }
-# })
-#setMethod("show", "Neighborhood",
-# function(object){
-# cat(paste("An object of class", dQuote(class(object)), "\n"))
-# cat("type:\t", object at type, "\n")
-# cat("radius:\t", object at radius, "\n")
-# })
-#setMethod("show", "FixRobModel",
-# function(object){
-# cat(paste("An object of class", dQuote(class(object)), "\n"))
-# cat("###### center:\t")
-# show(object at center)
-# cat("\n###### neighborhood:\t")
-# show(object at neighbor)
-# })
-#setMethod("show", "InfRobModel",
-# function(object){
-# cat(paste("An object of class", dQuote(class(object)), "\n"))
-# cat("###### center:\t")
-# show(object at center)
-# cat("\n###### neighborhood:\t")
-# show(object at neighbor)
-# })
-#setMethod("show", "RiskType",
-# function(object){
-# cat(paste("An object of class", dQuote(class(object)), "\n"))
-# cat("risk type:\t", object at type, "\n")
-# })
-#setMethod("show", "asUnOvShoot",
-# function(object){
-# cat(paste("An object of class", dQuote(class(object)), "\n"))
-# cat("risk type:\t", object at type, "\n")
-# cat("width:\t", object at width, "\n")
-# })
-#setMethod("show", "asHampel",
-# function(object){
-# cat(paste("An object of class", dQuote(class(object)), "\n"))
-# cat("risk type:\t", object at type, "\n")
-# cat("bound:\t", object at bound, "\n")
-# })
-#setMethod("show", "fiUnOvShoot",
-# function(object){
-# cat(paste("An object of class", dQuote(class(object)), "\n"))
-# cat("risk type:\t", object at type, "\n")
-# cat("width:\t", object at width, "\n")
-# })
-#setMethod("show", "fiHampel",
-# function(object){
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/robkalman -r 21
More information about the Robkalman-commits
mailing list