printForecastAccuracy(all.models[c("YA3nf", "YZ3nf", "MA3nf", "MZ3nf")], dm.pairs=rbind( c(1,2), c(3,4), c(2,4)), rmin=10/120000)
printForecastAccuracy(all.models[c("YA3nf", "YZ3nf", "MA3nf", "MZ3nf")], dm.pairs=rbind( c(1,2), c(3,4), c(2,4)), rmin=10/120000)
traceback()
printForecastAccuracy(all.models[c("YA3nf", "YZ3nf", "MA3nf", "MZ3nf")], dm.pairs=rbind( c(1,2), c(3,4), c(2,4)), rmin=10/120000)
printForecastAccuracy(all.models[c("YA3nf", "YZ3nf", "MA3nf", "MZ3nf")], dm.pairs=rbind( c(1,2), c(3,4), c(2,4)), rmin=10/120000)
printForecastAccuracy(all.models[c("YA3nf", "YZ3nf", "MA3nf", "MZ3nf")], dm.pairs=rbind( c(1,2), c(3,4), c(2,4)), rmin=10/120000)
printForecastAccuracy(all.models[c("YA3nf", "YZ3nf", "MA3nf", "MZ3nf")], dm.pairs=rbind( c(1,2), c(3,4), c(2,4)), rmin=10/120000)
printForecastAccuracy(all.models[c("YA2", "YZ2", "YA3", "YZ3", "MA1", "MZ1", "MA2", "MZ2")]) # original models
printForecastAccuracy(all.models[c("YA3nf", "YZ3nf", "MA3nf", "MZ3nf")], dm.pairs=rbind( c(1,2), c(3,4), c(2,4)), rmin=10/120000)
printForecastAccuracy(all.models[c("YA2", "YZ2", "YA3", "YZ3", "MA1", "MZ1", "MA2", "MZ2")]) # original models
printForecastAccuracy(all.models[c("YA2", "YZ2", "YA3", "YZ3", "MA1", "MZ1", "MA2", "MZ2")]) # original models
q()
source("results.r")
source("results.r")
source("results.r")
?match.arg
?match.arg
testForecastAccuracy(af.models$MA3)
testForecastAccuracy(af.models$MA3)
testForecastAccuracy(af.models$MA2)
testForecastAccuracy(af.models$MA2)
testForecastAccuracy(af.models$MA2)
testForecastAccuracy(af.models$MA2)
testForecastAccuracy(af.models$MA2)
testForecastAccuracy(af.models$MZ2)
testForecastAccuracy(models$MZ2)
testForecastAccuracy(models$MZ2)
testForecastAccuracy(models$MZ2)
testForecastAccuracy(models$MZ2)
testForecastAccuracy(models$MZ2)
testForecastAccuracy(models$MA2)
testForecastAccuracy(all.models$MA2)
f <- function(x) rep(x, 3)
f(2)
make.f <- function(N) function(x) rep(x, N)
f <- make.f(3)
f(2)
f(5)
g <- make.f(5)
g(2)
make.f <- function(N) function(x) seq(N, N+x)
f <- make.f(5)
f(1)
f(4)
make.f <- function(N) function(x) seq(x, N+x)
f <- make.f(5)
f(2)
f <- function(x) (make.f(5))(x)[3]
f(2)
printForecastAccuracy(all.models[c("YA2", "YZ2", "YA3", "YZ3", "MA1", "MZ1", "MA2", "MZ2")]) # original models
printForecastAccuracy(all.models[c("YA2", "YZ2", "YA3", "YZ3", "MA1", "MZ1", "MA2", "MZ2")]) # original models
printForecastAccuracy(all.models[c("YA2", "YZ2", "YA3", "YZ3", "MA1", "MZ1", "MA2", "MZ2", "MA3nf", "MZ3nf")])
names(all.models)
source("results.r")
traceback()
printForecastAccuracy(all.models[c("YA2", "YZ2", "YA3nf", "YZ3nf", "MA2", "MZ2", "MA3nf", "MZ3nf")])
printForecastAccuracy(all.models[c("YA2", "YZ2", "YA3nf", "YZ3nf", "MA2", "MZ2", "MA3nf", "MZ3nf")])
traceback()
printForecastAccuracy(all.models[c("YA2", "YZ2", "YA3nf", "YZ3nf", "MA2", "MZ2", "MA3nf", "MZ3nf")])
q()
install.packages("../R/mypackages/forecast_5.9.zip")
dm.test
library(forecast)
dm.test
source("results.r")
source("results.r")
i
h <- 24
names(models)
dmtest
dm.test
e1 <- dm.pairs[i, 1], , h]
e1 <- FEs[dm.pairs[i, 1], , h]
e2 <- FEs[dm.pairs[i, 2], , h]
cbind(e1, e2)
colMeans(abs(cbind(e1, e2)))
dm.test
power=1
d.var
d
Q
source("results.r")
source("results.r")
source("results.r")
)
d.var
cbind(e1, e2)
Q
setwd("../pred")
source("jps.r")
source("jps.r")
source("ln.r")
source("ln.r")
source("ln.r")
source("ln.r")
source("ln.r")
source("ln.r")
source("ln.r")
q()
source("results.r")
traceback()
getModelName(zlb.models$MZ2)
traceback()
source("results.r")
source("results.r")
traceback()
source("results.r")
source("results.r")
plotLiftoffDist(zlb.models$MZ2, plot.mode=0, date=20121231)
plotLiftoffDist(zlb.models$MZ2, plot.mode=0, date=20121231)
plotLiftoffDist(zlb.models$MZ2, plot.mode=0, date=20121231)
plotLiftoffDist(zlb.models$MZ2, plot.mode=0, date=20121231)
plotLiftoffDist(zlb.models$MZ2, plot.mode=0, date=20121231)
plotLiftoffDist(zlb.models$MZ2, plot.mode=2, date=20121231)
plotLiftoffDist(zlb.models$MZ2, plot.mode=2, date=20121231)
plotLiftoffDist(zlb.models$MZ2, plot.mode=2, date=20121231)
Q
q()
source("results.r")
plotPaths(model, plot.mode=0, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=0, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=0, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=0, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=0, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=0, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=0, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=0, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=plot.mode, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=0, plot.dates=c(20121231, 20131231))
plotPaths(model, plot.mode=plot.mode, plot.dates=c(20121231, 20131231))
graphics.off()
source("results.r")
source("results.r")
m <- model
corrMeasures(model)
q()
source("est_jsz_zlb.r")
source("est_jsz_zlb.r")
source("est_jsz_zlb.r")
pars2theta.jszk
source("est_jsz_zlb.r")
source("est_jsz_zlb.r")
source("est_jsz_zlb.r")
traceback()
names(res.llk)
q()
source("results.r")
plotLiftoffDist(zlb.models$MZ2, plot.mode=0, date=20121231)
zlb.models$MZ2
m <- zlb.models$MZ2
date=20121231
t
plotLiftoffDist(zlb.models$MZ2, plot.mode=0, date=20121231)
source("results.r")
traceback()
plotLiftoffDist(model, plot.mode=0, date=20121231)
plotLiftoffDist(model, plot.mode, date=20121231)
q()
source("est_jls_zlb.r")
0
theta.start
theta1 <- theta.start
pars2 <- theta2pars.jlsk(theta1)
theta2 <- pars2theta.jlsk(pars2)
cbind(theta1, theta2)
all.equal(theta1, theta2)
source("est_jls_zlb.r")
Q
0
source("est_jls.r")
0
0
source("est_jls_zlb.r")
Q
0
source("est_jls_zlb.r")
0
source("est_jls_zlb.r")
0
source("est_jls_zlb.r")
0
source("est_jls_zlb.r")
0
0
cN
pars$K1P
jls.kalman.zlb
debugonce(jls.kalman.zlb)
n
n
n
n
n
n
cN
cL
cM
formals(jls.kalman.zlb)
pars$cL
0
Q
0
pars$rho0
0
pars$rho0
names(loads)
0
0
cP
cM
cN
pars
file.save
q()
source("results.r")
source("results.r")
traceback()
traceback()
debug(analyzePace)
n
n
n
Q
options(error=recover)
undebug(analyzePace)
1
ls()
8
ls()
path
m
Q
0
0
source("results.r")
0
source("results.r")
0
source("results.r")
12
path
liftoff
Q
source("results.r")
source("est_jls.r")
0
source("est_jls.r")
Q
0
theta2pars.jlsk(theta)
0
0
0
install.packages("../R/mypackages/FKF_0.1.3.zip")
library(FKF)
0
options(error=NULL)
install.packages("../R/mypackages/RUnit_0.4.28.zip")
library(FKF)
source("est_jls.r")
help(fkf)
head(M.o/1200
)
source("est_jls.r")
jls.fkf
source("est_jls.r")
loads$A
GGt
round(GGt, 2)
round(GGt, 5)
round(GGt*10000, 5)
round(GGt*1000000, 5)
0
Q
source("est_jls.r")
0
Q
source("est_jls.r")
?KalmanRun
KalmanRun
source("est_jls.r")
source("results.r")
source("results.r")
source("results.r")
source("results.r")
source("results.r")
source("results.r")
setwd("../pred")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
NeweyWest
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
coefs <- rval$coefs
names(rval)
print(rval)
source("stambaugh.r")
source("stambaugh.r")
names(mods[[1]])
names(summary(mods[[1]]))
?summary.lm
vcov
stats::vcov
stats::vcov.lm
stats:::vcov.lm
summary(SEs)
str(SEs)
str(coefs)
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
source("stambaugh.r")
q()
source("results.r")
traceback()
source("results.r")
sink()
source("results.r")
?points
graphics.off()
plotLiftoffNew(model, plot.mode=0)
plotLiftoffNew(model, plot.mode=0)
?legend
source("est_jls.r")
names(rval)
str(pars$cP)
source("results.r")
source("results.r")
source("results.r")
source("results.r")
source("results.r")
q()
library(utilities)
getOptim
source("results.r")
source("results.r")
q()
source("results.r")
getOptim
names(model)
source("results.r")
 names(all.models)
ma2 <- all.models$MA2
mz2 <- all.models$MZ2
colMeans(ma2$Y.hat)
colMeans(mz2$Y.hat)
colMeans(ma2$Y.hat)*1200
colMeans(mz2$Y.hat)*1200
ma2$Phi
mz2$Phi
str(ma$cP)
str(ma2$cP)
str(mz2$cP)
head(ma2$cP)
head(mz2$cP)
ma2$lamQ
mz2$lamQ
options(error=NULL)
source("results.r")
source("results.r")
source("results.r")
source("results.r")
source("est_jls.r")
getOptim
source("est_jls.r")
source("est_jls.r")
source("est_jls.r")
warnings()
source("est_jls.r")
source("results.r")
source("results.r")
q()
source("results.r")
q()
source("results.r")
sink()
source("results.r")
str(lapply)
str(tmp)
str(tmp)
colnames(tmp)
head(tmp)
tail(tmp)
q()
source("results.r")
printForecastAccuracy(all.models, to.latex, dm.pairs=rbind( c(1,2), c(3,4), c(1, 3), c(2,4)))
printForecastAccuracy(all.models, to.latex, dm.pairs=rbind( c(1,2), c(3,4), c(1, 3), c(2,4)))
i
i
h
dm.test2
dm.test
debugonce(dm.test2)
n
n
n
n
n
n
dv
d
h-1
d.cov
d.cov[1]
sum(c(d.cov[1], 2 * d.cov[-1]))
c
rval
names(rval)
rval$statistic
Q
printForecastAccuracy(all.models, to.latex, dm.pairs=rbind( c(1,2), c(3,4), c(1, 3), c(2,4)))
source("results.r")
source("results.r")
source("results.r")
source("results.r")
q()
source("results.r")
traceback90
traceback()
plotData()
plotData(plot.mode)
plotData(plot.mode)
dev.off()
plotViolations(af.models, plot.mode)
plotViolations(af.models, plot.mode)
plotShadowWedge(model, plot.mode=plot.mode)
plotShadowWedge(model, plot.mode=plot.mode)
plotShadowWedge(model, plot.mode=plot.mode)
dev.off()
dev.off()
dev.off()
dev.off()
plotShadowWedge(model, plot.mode=plot.mode)
plotShadowWedge(model, plot.mode=plot.mode)
plotShadowWedge(model, plot.mode)
mats
plotViolations(af.models, plot.mode)
q()
source("results.r")
traceback()
ccccccc
source("
q()
source("zlb.r")
q()
source("results.r")
str(df)
mats
colnames(Y)
str
str(df)
str(df)
str(df)
sum(post.2007)
surveys
surveys
surveys
A
names(surveys)
Q
A
A
Q
str(model)
str(df)
str(df)
df
str(df)
length(df)
tm
q()
source("results.r")
traceback()
str(df)
str(df)
q()
setwd("data_and_code_public")
source("est_jsz.r")
source("est_jsz.r")
source("est_jls.r")
q()
source("est_jls.r")
source("est_jsz.r")
source("results.r")
source("results.r")
source("results.r")
q()
