Nothing
require("Xtratsfa")
data("CanadianMoneyData.asof.6Feb2004", package="CDNmoney")
#require("dse")
#require("EvalEst") # for EstEval
fuzz <- 1e-6
all.ok <- TRUE
### Construct data
cpi <- 100 * M1total / M1real
seriesNames(cpi) <- "CPI"
popm <- M1total / M1PerCapita
seriesNames(popm) <- "Population of Canada"
z <- tframed(tbind(
MB2001,
MB486 + MB452 + MB453 ,
NonbankCheq,
MB472 + MB473 + MB487p,
MB475,
NonbankNonCheq + MB454 + NonbankTerm + MB2046 + MB2047 + MB2048 +
MB2057 + MB2058 + MB482),
names=c("currency", "personal cheq.", "NonbankCheq",
"N-P demand & notice", "N-P term", "Investment")
)
z <- tfwindow(z, start=c(1986,1))
if( all(c(2003,12) ==end(z))) z <-tfwindow(z, end=c(2003,11))
MBcomponents <- 1e8 * z/matrix(tfwindow(popm * cpi,tf=tframe(z)), Tobs(z),6)
### Specify "true" parameters and factors
Omega <- diag(c(72.633490218431234, 1233.026245431895177, 87.337721037020572,
629.392699084312198, 3967.982989812266169, 12163.258995566555313))
Boblq <- t(matrix(c(
8.8424730199723260, 5.2034757439511159,
23.8239003553122046, -12.5767326858555819,
5.1878379834837549, -1.9710231572687940,
36.7834439249370746, 16.9430526918934632,
-2.8494845070603847, 31.0224248853059343,
2.6047417719514878, 47.6304267232332990), 2,6))
PhiOblq <- t(matrix(c(
1.0000000000000002220, 0.0094910545788177599,
0.0094910545788177599, 1.0000000000000002220),2,2))
etaBart <- MBcomponents %*% solve(Omega) %*% Boblq %*% (
solve( t(Boblq) %*% solve(Omega) %*% Boblq ) )
DetaBart <- diff(etaBart, lag=1)
SDE <- cov(DetaBart)
RR1 <- chol(SDE) # upper triangular: SDE = RR1' RR1
RR2 <- chol(PhiOblq) # ditto
PP <- t(RR2) %*% solve(t(RR1))
etaTrue <- tframed(etaBart %*% t(PP), tf=tframe(MBcomponents))
Psi <- 0.5 * Omega
rngValue10 <- list(seed=10, kind="Mersenne-Twister", normal.kind="Inversion")
######## replace with simulate
# oldrng <- setRNG(rngValue10) # do this to be able to reproduce the result
# simBoblq <- tframed(etaTrue %*% t(Boblq) +
# matrix(rnorm(215*6),215,6) %*% Psi^0.5, tframe(etaTrue))
# attr(simBoblq, "TSFmodel") <- TSFmodel(Boblq, f=etaTrue, positive.measures=FALSE)
########
simBoblq <- simulate(TSFmodel(Boblq, f=etaTrue,
positive.measures=FALSE), Cov=Psi, rng=rngValue10) #, noIC=TRUE)
### Tests to check that calculated values have not changed
R2M <- estTSF.R2M(simBoblq, 2, BpermuteTarget=Boblq)
## estTSF.R2M
# tst <- diag(c(77.99645, 748.9573, 99.53656, 415.0742, 3398.993, 15744.05))
tst <- diag(c(77.996445788386325, 748.957233304161718, 99.536559405226782,
415.074278197450212, 3398.993363841897008, 15744.044865312540423))
# above was with noIC=TRUE
tst <- diag(c(60.1921658615183119, 1521.92750673138289, 80.1775315356583462,
538.78541161218584, 3278.92245163269126, 13716.5150374459536))
if( fuzz < max(abs( TSFmodel(R2M)$Omega - tst ))) {
cat("Calculated value is not the same as test value in test R2M Omega. Value:\n")
printTestValue(diag(TSFmodel(R2M)$Omega), digits=18)
cat("difference:\n")
print(TSFmodel(R2M)$Omega - tst, digits=18)
all.ok <- FALSE
}
# using early version of GPA (which had maxit=500, eps=1e-5, and possibly did
# normalizing by default)
# tst <- t(matrix(c(
# 9.5827796079501262, 1.194853488131824,
# 18.3146972876954202, -27.064310418133847,
# 4.3641559737993809, -3.965655542475369,
# 41.8253613768086652, 10.727641838770557,
# 7.2454495413908111, 22.659136649733295,
# 11.0746701624519517, 43.028949876914211), 2,6))
tst <- t(matrix(c(
9.58279926941862747 , 1.19468110010036321 ,
18.3141811702646855 , -27.064649111931633 ,
4.36407984329363074 , -3.96573546828498991,
41.8255511946882521 , 10.7268911600826318 ,
7.24587486298229511 , 22.6590131466900822 ,
11.0754786411397301 , 43.028763740921562 ), 2,6))
# above was with noIC=TRUE
tst <- t(matrix(c(
8.30417180888775697 , 5.9189517689730069 ,
19.2899646003996743 , -1.10169539929101057 ,
6.78784954005505003 , -2.99664699926621569 ,
30.1804808001785112 , 27.0028414319191192 ,
-0.0226193992892303811 , 29.1059985036404107 ,
-9.99041567888333937 , 55.5319485924123271), 2,6))
if( fuzz < max(abs( loadings(TSFmodel(R2M)) - tst ))) {
cat("Calculated value is not the same as test value in test R2M B. Value:\n")
printTestValue(loadings(TSFmodel(R2M)) , digits=18)
cat("difference:\n")
print(loadings(TSFmodel(R2M)) - tst, digits=18)
all.ok <- FALSE
}
tst <- t(matrix(c(
0.020023526108538952, 0.00581641466686578981, 0.00926283108801265534,
0.0158018466954418756, 4.83143348135837777e-05, -8.97171237737207903e-06,
0.00346727161930753675, -0.0228639823708243414, -0.0259972997881601428,
0.0108268112952340824 , 0.00390757155775263605 , 0.00160995131439499038), 6,2))
# above was with noIC=TRUE
tst <- t(matrix(c(
0.029012912423980592 , 0.00646674389461628866 , 0.0558705582001856327 ,
0.00780976386778681718 , -0.00346133050041043258, -0.00193253873557866561,
0.0156845837155822933 , -0.0054485846455110936 , -0.0593682414836703906,
0.0135641196765327893, 0.00627000005559145979, 0.00314217277690974957), 6,2))
if( fuzz < max(abs(R2M$LB - tst ))) {
cat("Calculated value is not the same as test value in test R2M LB. Value:\n")
printTestValue(R2M$LB, digits=18)
cat("difference:\n")
print(R2M$LB - tst, digits=18)
all.ok <- FALSE
}
cat("tests completed.\n")
if (! all.ok) stop("some tests FAILED")
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