[Depmix-commits] r116 - trunk/srcll
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Mar 27 23:27:52 CET 2008
Author: ingmarvisser
Date: 2008-03-27 23:27:52 +0100 (Thu, 27 Mar 2008)
New Revision: 116
Removed:
trunk/srcll/.Rhistory
Log:
Removed .Rhistory
Deleted: trunk/srcll/.Rhistory
===================================================================
--- trunk/srcll/.Rhistory 2008-03-27 22:26:51 UTC (rev 115)
+++ trunk/srcll/.Rhistory 2008-03-27 22:27:52 UTC (rev 116)
@@ -1,569 +0,0 @@
-n
-x
-length(x)
-cfunction
-compileCode
-inline:::compileCode
-?match
-match
-library(dlm)
-?dlm
-## seasonal component for quarterly data#
-dlmModSeas(4, dV = 3.2)
-x <- matrix(runif(6,4,10), nc = 2); x
-dlmModReg(x)
-dlmModReg(x, addInt = FALSE)
-data(NelPlo)#
-### multivariate local level -- seemingly unrelated time series#
-buildSu <- function(x) {#
- Vsd <- exp(x[1:2])#
- Vcorr <- tanh(x[3])#
- V <- Vsd %o% Vsd#
- V[1,2] <- V[2,1] <- V[1,2] * Vcorr#
- Wsd <- exp(x[4:5])#
- Wcorr <- tanh(x[6])#
- W <- Wsd %o% Wsd#
- W[1,2] <- W[2,1] <- W[1,2] * Wcorr#
- return(list(#
- m0 = rep(0,2),#
- C0 = 1e7 * diag(2),#
- FF = diag(2),#
- GG = diag(2),#
- V = V,#
- W = W))#
-}
-head(NelPlo)
-head(NelPlo,30)
-dim(NelPlo)
-NelPlo
-dlmMLE
-dlmLL
-library(rdonlp2)
-library(rdonlp)
-library(Rdonlp)
-library(rdonlp2)
-library(Rdonlp2)
-?Rdonlp2
-?Rdonlp
-?rdonlp
-help(pack="Rdonlp2")
-?donlp2
-library(depmix)
-?depmix
-data(speed)#
-mod <- dmm(nsta=2,itemt=c(1,2)) # gaussian and binary items#
-fit1 <- fitdmm(dat=speed,dmm=mod)
-?donlp2
-library(Rdonlp2)
-y=library(Rdonlp2)
-y
-datasets
-y$datasets
-?datasets
-library(depmix)
-?depmix
-data(speed)#
-mod <- dmm(nsta=2,itemt=c(1,2)) # gaussian and binary items#
-fit1 <- fitdmm(dat
-=speed,dmm=mod)
-summary(fit1)
-library(depmix)
-?depmix
-library(Rhmm)
-?Rhmm
-?HMMSet
-library(RHmm)
-?RHmm
-?HMMSet
- data(geyser)#
- obs <- geyser$duration
-head(geyse)
-head(geyser)
-plot(as.ts(geyser$waiting))
-plot(as.ts(geyser$duration))
-plot(as.ts(geyser[1:50,]))
-plot(as.ts(geyser[1:100,]))
-cor(geyser)
- ResGeyser1 <- HMMFit(obs)
- ResGeyser2 <- HMMFit(obs, nStates=3, paramBW=list(verbose=1, init="KMEANS"))#
- # fit a 2 states of a mixture of 3 normal distributions#
- # for data_mixture#
- data(data_mixture)#
- ResMixture <- HMMFit(data_mixture, nStates=2, nMixt=3, dis="MIXTURE")#
- summary(ResMixture)#
- # geyser data - 3 states HMM with bivariate normal distribution#
- ResGeyser<-HMMFit(obs=as.matrix(geyser), nStates=3)#
- # multiple samples discrete observations#
- data(weather)#
- ResDiscrete <- HMMFit(obs=weather, nStates=3, dis="DISCRETE")
-ResDiscrete
-library(nnet)
-?multinom
-multinom
-library(depmixS4)
-?depmix
- data(speed)#
- depmix(list(rt~1,corr~1),data=speed,nstates=2,family=list(gaussian(),multinomial()))
-mod <- depmix(list(rt~1,corr~1),data=speed,nstates=2,family=list(gaussian(),multinomial()))
- mod
- # create a 2 state model with one continuous and one binary response
- data(speed)
- mod <- depmix(list(rt~1,corr~1),data=speed,nstates=2,family=list(gaussian(),multinomial()))
- # print the model, formulae and parameter values
- mod
-?library
-library(depmixS4)
-?depmix
-?stats4
-library(stats4)
-?stats4
-?statmodel
-library(modeltools)
-?fit
-methods(fit)
-getAnywhere(fit)
-fit[depmixS4]
-fit[1]
-[2]
-modeltools:::fit
-depmixS4:::fit
-depmix
-?depmix
-?depmix.fit
-fit
- data(speed)
- # 2-state model on the RTs of the speed data with random
- # starting values for the transition pars (without those EM does not get off the ground)
- set.seed(1)
- mod <- depmix(rt~1,data=speed,nstates=2,trstart=runif(4))
- # fit the model
- mod1 <- fit(mod)
- mod1 # to see the logLik and optimization information
- # to see the parameters
- summary(mod1)
-mod
-library(modeltools)
-library(depmixS4)
-?depmix.fit
-ls()
-?depmix-class
-?"depmix-class"
-library(depmixS4)
-?"depmix-class"
-?depmix.fit
-library(depmixS4)
-?depmix.fit
-data(speed)#
-# 2-state model on the RTs of the speed data with random #
-# starting values for the transition pars (without those EM does not get off the ground)#
-set.seed(1)#
-mod <- depmix(rt~1,data=speed,nstates=2,trstart=runif(4))#
-# fit the model#
-mod1 <- fit(mod)
-mod1
-summary(mod1)
-?depmix
-?llratio
-library(depmixS4)
-?llratio
-?depmix
-library(depmixS4)
-?llratio
-library(depmixS4)
-?llratio
-library(depmixS4)
-?llratio
-?balance
-posterior
-?balance
-library(flexmix)
-?flexmix
-?balance
-?flexmix
-?response-class
-?"response-class"
-?speed
-data(speed)
-head(speed)
-head(speed,24)
-max(speed$Pacc)
-?"response-classes"
-?"response-class"
-?glm
-library(depmixS4)
-?balance
-?"depmix-class"
-?em
-?"depmix.fi"
-?"depmix.fit"
-?depmix
-mod
-
-# to see the ordering of parameters to use in setpars
-mod <- setpars(mod, value=1:npar(mod))
-mod
-# create a 2 state model with one continuous and one binary response
-data(speed)
-mod <- depmix(list(rt~1,corr~1),data=speed,nstates=2,family=list(gaussian(),multinomial()))
-# print the model, formulae and parameter values
-mod
-
-# to see the ordering of parameters to use in setpars
-mod <- setpars(mod, value=1:npar(mod))
-mod
-mod <- setpars(mod, getpars(mod,which="fixed"))
-mod
-?llratio
-?"response-class"
-?GLMresponse-class
-?"GLMresponse-class"
-?glm
-?response
-library(depmixS4)
-
-x <- rnorm(100)
-xd <- data.frame(x,1)
-
-mod <- depmix(x~1,ns=2,nt=100,trst=runif(4))
-
-viterbi(mod)
-fm <- fit(mod)
-
-viterbi(fm)
-data(speed)
-rt <- speed$rt
-
-mod <- depmix(rt~1,ns=2,nt=439,trst=runif(4))
-
-fm <- fit(mod)
-
-viterbi(fm)
-viterbi
-library(depmixS4)
-data(speed)
-rt <- speed$rt
-
-mod <- depmix(rt~1,ns=2,nt=439,trst=runif(4))
-
-fm <- fit(mod)
-
-viterbi(fm)
-viterbi
-library(depmixS4)
-data(speed)
-rt <- speed$rt
-
-mod <- depmix(rt~1,ns=2,nt=439,trst=runif(4))
-
-fm <- fit(mod)
-
-viterbi(fm)
-plot(as.ts(viterbi(fm))
-)
-plot(as.ts(viterbi(fm)))
-trstart=c(0.899,0.101,0.084,0.916)
-instart=c(0.5,0.5)
-resp <- c(5.52,0.202,0.472,0.528,6.39,0.24,0.098,0.902)
-
-mod <- depmix(list(rt~1,corr~1),data=speed,nstates=2,family=list(gaussian(),multinomial()),trstart=trstart)
-# respstart=resp,trstart=trstart,instart=instart)
-
-logLik(mod)
-
-mod1 <- fit(mod)
-ll <- logLik(mod1)
-
-
-#
-# Test optimization using Rdonlp2
-#
-
-trstart=c(0.899,0.101,0,0.01,0.084,0.916,0,0)
-instart=c(0.5,0.5)
-resp <- c(5.52,0.202,0.472,0.528,6.39,0.24,0.098,0.902)
-
-mod <- depmix(list(rt~1,corr~1),data=speed,transition=~Pacc,nstates=2,family=list(gaussian(),multinomial()),
- respstart=resp,trstart=trstart,instart=instart)
-
-logLik(mod)
-
-mod1 <- fit(mod)
-ll <- logLik(mod1)
-post <- cbind(viterbi(mod1),speed$Pacc)
-plot(as.ts(post))
-cor(post)
-mod at ntimes
-mod1 at ntimes
-plot(rnorm(100))#
-par(fig=c(0, 1/2, 0, 1/2), new=T)#
-plot(seq(-2,2,length=300),dnorm(seq(-2,2,length=300)),type="l", axes =#
-F, xlab="", ylab="")
-A <- matrix(1:4,2,2)
-B <- matrix(1:10,10)
-init <- matrix(1:2,1)
-A
-B
-init
-ct <- A*B
-apply(B,1,prod,A)
-apply(B,1,,A)
-A*B[1,]
-apply(B,1,*,A)
-apply(B,1,"*",A)
-?array
-ct <- array(apply(B,1,"*",A),c(2,2,10))
-ct
-library(depmixS4)
-
-data(speed)
-mod <- depmix(list(rt~1,corr~1),data=speed,nstates=2,family=list(gaussian(),multinomial()))
-# print the model, formulae and parameter values
-mod
-
-x=lystig(mod at init,mod at trDens,apply(mod at dens,c(1,3),prod),mod at ntimes)
-x
-setwd("/Users/ivisser/Documents/projects/depmixProject/depmixNew/rforge/depmix/trunk/srcll")
-source("lystig2.R")
-x1=lystig(mod at init,mod at trDens,apply(mod at dens,c(1,3),prod),mod at ntimes)
-
-source("lystig2.R")
-
-x2=lystig(mod at init,mod at trDens,apply(mod at dens,c(1,3),prod),mod at ntimes)
-
-all.equal(x1,x2)
-x1=lystig(mod at init,mod at trDens,apply(mod at dens,c(1,3),prod),mod at ntimes)
-
-source("lystig2.R")
-
-x2=lystig(mod at init,mod at trDens,apply(mod at dens,c(1,3),prod),mod at ntimes)
-
-all.equal(x1,x2)
-x1=lystig(mod at init,mod at trDens,apply(mod at dens,c(1,3),prod),mod at ntimes)
-x1b=lystig(mod at init,mod at trDens,apply(mod at dens,c(1,3),prod),439)
-
-
-source("lystig2.R")
-
-x2=lystig(mod at init,mod at trDens,apply(mod at dens,c(1,3),prod),mod at ntimes)
-x2b=lystig(mod at init,mod at trDens,apply(mod at dens,c(1,3),prod),439)
-
-all.equal(x1,x2)
-all.equal(x1b,x2b)
-A <- matrix(1:4,2,2)
-B <- matrix(1:10,5)
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(2,2,10))
-ct
-B
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(2,2,10))
-A
-B
-ct
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(2,2,5))
-ct
-A
-B
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(2,2,5),byrow=T)
-?array
-methods(summary)
-showMethods(summary)
-A[1,]*B[1,]
-A[2,]*B[1,]
-apply(B,1,"*",A),c(2,2,5)
-apply(B,1,"*",A)
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(2,5,2)
-)
-ct
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(2,2,5))
-
-ct <- array(apply(B,1,"*",A),c(5,2,2))
-
-ct
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(2,2,5))
-
-ct <- array(apply(B,1,"*",A),c(5,2,2))
-
-ct[1,]
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(2,2,5))
-
-ct <- array(apply(B,1,"*",A),c(5,2,2))
-
-ct[1,,]
-
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(5,2,2))
-
-ct[1,,]
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(5,2,2))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-A[1,]*B[1,]
-A[2,]*B[1,]
-A <- matrix(1:4,2,2)
-
-B <- matrix(1:10,5)
-
-init <- matrix(1:2,1)
-
-ct <- array(apply(B,1,"*",A),c(5,2,2))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-ct <- array(apply(B,1,"*",A),c(2,5,2))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-ct <- array(apply(B,1,"*",A),c(2,2,5))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-ct <- array(apply(A,1,"*",B),c(2,2,5))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-ct <- array(apply(A,1,"*",B),c(2,5,2))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-ct <- array(apply(A,1,"*",B),c(5,2,2))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-A[1,]*B[1,]
-A[2,]*B[1,]
-ct <- array(apply(A,1,"*",B),c(5,2,2))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-
-
-A[1,]*B[1,]
-A[2,]*B[1,]
-t(ct)
-ct <- array(apply(A,1,"*",B),c(5,2,2))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-
-
-A[1,]*B[1,]
-A[2,]*B[1,]
-
-A[1,]*B[2,]
-A[2,]*B[2,]
-ct[2,,]
-ct <- array(apply(t(A),1,"*",B),c(5,2,2))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-
-
-A[1,]*B[1,]
-A[2,]*B[1,]
-ct <- array(apply(A,1,"*",B),c(5,2,2))
-
-ct[1,,]
-ct[,1,]
-ct[,,1]
-
-
-A[1,]*B[1,]
-A[2,]*B[1,]
-sessionInfo()
-A <- array(1:20,c(5,2,2))
-
-B <- matrix(1:10,5)
-A
-B
-A <- array(1:20,c(2,2,5))
-A
-B <- matrix(1:10,5)
-B
-rbind(A[1,]*B[1,],
-A[2,]*B[1,])
-
-rbind(A[1,,1]*B[1,],
-A[2,,1]*B[1,])
-rbind(A[1,,2]*B[2,],
-A[2,,2]*B[2,])
-rbind(A[1,,3]*B[2,],
-A[2,,3]*B[2,])
-apply(B,1,"*",A)
-c(sort(apply(B,1,"*",A)))
-ct <- numeric(0)
-for(i in 1:5){
-ct <- c(ct,(A[1,,i]*B[1,],
-A[2,,i]*B[1,])
-}
-ct <- numeric(0)
-ct
-ct <- numeric(0)
-for(i in 1:5){
-ct <- c(ct,A[1,,i]*B[1,],A[2,,i]*B[1,])
-}
-ct
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