How can i compute multi-dimension mean matrix?
0
I want to compute dynamic conditional correlation(dcc) mean matrix at all time.
Rho is each day matrix.
but i want to make a mean matrix all day (not each day)
this is DCC-garch model.
library(rugarch)
library(rmgarch)
library(xts)
stockdata<-read.zoo("C:\Users\Taehee Cha\Desktop\\data\EUCall.csv",
header=TRUE,
sep=",",
format = "%Y-%m-%d",
nrow=4433)
stock_xts<-as.xts(stockdata,dateFormat='POSIXct')
DKOSPI200 <-diff(log(stock_xts$KOSPI200))*100
DDAX30 <-diff(log(stock_xts$DAX30))*100
DSNP500 <-diff(log(stock_xts$SNP500))*100
DFTSE100 <-diff(log(stock_xts$FTSE100))*100
...
data2<-data.frame(DKOSPI200,DDAX30,DSNP500,DFTSE100,DEUROSTOXX50,DFTSEMIB,DNIKKEI225,DSNPTSX,DCAC40,DJSE40,
DRTS,DIPC,DBOVESPA,DTadawul,DMERV,DSENSEX,DJSX,DSSE,DXU100,DSNPASX,
DATHEX,DAEX,DOBX,DSNPNZ50,DTAIEX,DOMXC20,DKLCI,DBEL20,DOMXS30,DSMI,
DIBEX,DSTI,DADX,DISEQ,DATX,DTA35,DEGX30,DPX50,DIPSA,DQE,
DIGBC,DSET,DKarachi100,DSNPBVL,DPSI20,DWIG20,DOMXH25,DPSEI,DBUX,DHANGSENG)
Univarate GARCH specification
gjrGARCH.spec <-ugarchspec(variance.model=list(model="gjrGARCH",garchOrder=c(1,1)),mean.model=list(armaOrder=c(1,0)))
Multivarate GARCH specification
dcc.gjrGARCH.spec=dccspec(uspec=multispec(replicate(50,gjrGARCH.spec)),
dccOrder=c(1,1),
distribution="mvnorm")
OUTCOME=dccfit(dcc.gjrGARCH.spec, data=data2)
Fit<-fitted(OUTCOME)
Sigma<-sigma(OUTCOME)
Rho<-rcor(OUTCOME)
dim(Rho)
>50 50 4432
I tried this, but I failed.
dccmean<-apply(Rho, c(1:4432), mean)
Error message:
Error in if (d2 == 0L) { : missing value where TRUE/FALSE needed
please help me....
> dput(head(data2))
structure(list(KOSPI200 = c(-0.64107155376405, -2.63428514277591,
-3.02361881202007, -0.348129159251176, -0.8463497185911, 0.933495693605124
), DAX30 = c(-0.275158289647415, -2.31165589473132, 0.132288230298805,
-0.916302412003311, -0.249954511741102, 1.5067409708557), SNP500 = c(0,
-1.23978129442266, -2.37787312356224, 0.68553903957973, -1.45026278352685,
-0.113477591886735), FTSE100 = c(-0.912643889420117, -1.27612498082748,
-0.189622000351441, -0.0175554735125871, -1.40042215908522, 1.65029716900129
), EUROSTOXX50 = c(-0.693995680230763, -2.63873467285407, 0.0340923169277474,
-1.10692637764913, -1.45688992650648, 0.90690109636018), FTSEMIB = c(-0.207307997135331,
-2.20987523065315, 0.11929602916414, -0.591164923299203, -1.23334692081265,
0.0674451667508791), NIKKEI225 = c(-0.172132904979705, -2.41825620786038,
-0.541031623946608, 0.494946220458736, -2.43002026761108, 3.30050037277818
), SNPTSX = c(-0.228827286223954, -0.618158165738869, -1.163192751949,
0.611234081963197, -1.07887096999253, 0.15982056970163), CAC40 = c(-0.996225333005363,
-2.45923020374033, 0.558708030675348, -1.07932737047562, -1.18770661796788,
0.946736097241008), JSE40 = c(-1.24801019778307, -0.660388491185593,
-0.378077731086712, 1.12913917165454, -0.270357667812782, 0.925230160391344
), RTS = c(1.69252595201295, -2.47912051247043, -1.68278329224893,
-0.628193976078784, -5.81832854668214, 2.33324601133127), IPC = c(0.410660821053099,
-0.793221688816637, -1.46058560736098, -0.0995162816563422, 0.0582618177329408,
-2.24304020680233), BOVESPA = c(-2.08399544316435, -0.0640501036023977,
-1.00884481719454, 0, -2.45326225130107, 1.76775969319749), Tadawul = c(-0.0751612871260576,
1.06988441714364, 0.467558379080923, 0.015629948658713, -0.479468927554549,
0.115645625170213), MERV = c(-0.812834284218145, -3.48526114996641,
-0.789176542098158, 0, -6.3347627637631, -2.25802417775345),
SENSEX = c(0.173466860804083, -0.357822108056638, -0.45387164272519,
1.1318914393021, 1.4301129114795, 2.24172363852979), JSX = c(0.464645515331874,
0.433624214120076, 0.382746462253802, 0.245017602482989,
0.417626097951018, 0.919117215344212), SSE = c(-0.9304947624722,
-0.512019911931727, -0.0399062163143782, 0.923519675548068,
-0.965701174169897, -0.149922817153048), XU100 = c(0.83997183599358,
-9.44220433432204, -1.19486088286003, -5.93037167728525,
-8.13019316543659, 4.39805147087551), SNPASX = c(-1.52481837941529,
-0.710076219124112, -0.355441763724151, 0.43889183264465,
0.632546988595983, 0.431277069387725), ATHEX = c(0.217251999604962,
-0.113093185749946, -4.08702446400842, -1.49759637062132,
-2.89449541976028, 2.84821759239637), AEX = c(-0.302724751872496,
-1.93350674725812, -0.334531789971226, -0.27844233175518,
-1.47467944242914, 0.59320521917563), OBX = c(-0.633345799178109,
-0.0872437271016935, -0.0686020794624653, -0.751459482064121,
-0.314782430663918, -0.138818800687446), SNPNZ50 = c(-0.589289243578772,
-0.212470628567818, -1.09525597597484, 1.56062961309287,
-0.594970797797778, 0.308439154148132), TAIEX = c(-0.634186259073921,
-0.0465155309724352, -1.06170058328026, -0.875355087660168,
-1.4930992055346, 1.85698166429091), OMXC20 = c(0.0415607672345608,
-0.892547743122307, 0.895744009882993, 0.00639222705407505,
-0.515886239547392, -0.744864387047794), KLCI = c(3.12710622798287,
1.55475618644338, 0.141888091655584, -0.2344629562125, -1.32130772048118,
-1.3324408754646), BEL20 = c(0.916239489510673, -0.838871120292239,
-0.349848101836958, 0.131119279926573, -0.220949965581685,
0.925072128183135), OMXS30 = c(-2.30694346428235, -3.59314374436401,
-0.132526843920378, -0.26558175544098, -0.700219536449254,
2.21356560948696), SMI = c(-0.923178651961543, -1.9888683347407,
0.190440901601185, -1.31581319814948, -1.24166996356809,
1.74938111396603), IBEX = c(-1.10228247337272, -3.30519689438287,
0.28541077977593, -0.719194686241131, -2.37890150982238,
-1.20979032592885), STI = c(-0.376825693193794, -1.56959227075815,
-0.209405887533087, 1.59189359203387, -0.998471722830718,
0.524545937488519), ADX = c(0, 0.234110707042312, -0.140988509294804,
-0.107833632972643, -0.00392341494084292, 0), ISEQ = c(-0.497210204416199,
-1.28827940816549, 1.05427460869301, 0.691923594974142, -1.2985333059083,
1.05885040639215), ATX = c(0.196176688098504, -0.397720264421864,
0.765032409498989, 0.634860192671294, -0.718109388684507,
0.288191756274081), TA35 = c(-0.467643907976623, -1.6933214269244,
0.638360404963567, 1.66873087937374, -1.03207784150818, 1.98476257832283
), EGX30 = c(-1.60808620054533, 0.486603179063838, 0.042060989053283,
-0.582335360174024, -1.05485347621963, 0.329916835288824),
PX50 = c(0, 0, -1.53717800478548, -0.567132576686191, -1.79645549752987,
0.100654261140143), IPSA = c(0.561439712306022, 0.849792667039129,
-0.327031029818503, -0.154168073702365, -0.737696755949457,
-0.476817106576277), QE = c(0.124155575561335, -0.299696872832733,
-0.087886339332055, 0.0366286953290995, 0.109805655043083,
0.0585137524009127), IGBC = c(0.151884596926966, -0.461362987666014,
1.12811837108895, 0.0931901841028981, 0.149517561508272,
0.312176099410877), SET = c(-0.475964725298805, 0, -0.126280143061397,
-0.243770852799319, -3.47030045650181, 0.752026997121558),
Karachi100 = c(-1.2595250361283, -1.09859841657665, -0.467295948347779,
-0.176282035250352, 1.06144685237481, 0.614077017080827),
SNPBVL = c(-0.0916272845215893, -0.488603970907153, -0.635609686024718,
0.72544080956467, -1.05989054433602, -0.290056131898186),
PSI20 = c(-0.498150623441695, -2.4995090145449, -0.916173928749231,
0.134620833204835, -1.96674118284665, 0.125363501017972),
WIG20 = c(-0.186154209522993, 2.29090171954054, -1.21234613135197,
-2.35741884661973, -1.39537944100319, 4.04050146384076),
OMXH25 = c(-0.734161177012371, -3.2781107280087, -0.274240630336653,
0.164265778301331, -2.88555610228327, 0.0196123710402674),
PSEI = c(1.16491407781849, -0.379401344663943, 0.604503127264966,
-0.551543468404248, -0.542372265371061, 0.668217806598204
), BUX = c(0.745432319945749, -0.407296683745706, 1.4847908668413,
-1.73656177766137, -1.70838647119353, 0.642365839539494),
HANGSENG = c(-1.58777648289217, 0, -2.40414908704771, 0.182801734695737,
-1.47377260414583, 1.05050572830176)), row.names = c("2001-07-05",
"2001-07-06", "2001-07-09", "2001-07-10", "2001-07-11", "2001-07-12"
), class = "data.frame")
I think it will be more useful to solve my problem.
dim(Rho)
>50 50 4432
> dput(head(Rho))
c(1, 0.28274756492168, 0.366762864615763, 0.287187938929745,
0.279313675150249, 0.25099353597608)
> str(Rho)
num [1:50, 1:50, 1:4432] 1 0.283 0.367 0.287 0.279 ...
- attr(*, "dimnames")=List of 3
..$ : chr [1:50] "KOSPI200" "DAX30" "SNP500" "FTSE100" ...
..$ : chr [1:50] "KOSPI200" "DAX30" "SNP500" "FTSE100" ...
..$ : chr [1:4432] "2001-07-05" "2001-07-06" "2001-07-09" "2001-07-10" ...
My questions
#, , "2001-07-05"
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 1 5 9 13
#DAX30 2 6 10 14
#SNP500 3 7 11 15
#FTSE100 4 8 12 16
#, , "2001-07-06"
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 1 5 9 13
#DAX30 2 6 10 14
#SNP500 3 7 11 15
#FTSE100 4 8 12 16
##----->I want to this ((ex)sum)
#, ,
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 2 10 18 26
#DAX30 4 12 20 28
#SNP500 6 14 22 30
#FTSE100 8 16 24 32
r multidimensional-array apply mean correlation
asked Nov 20 at 13:24
차태희
62
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show 3 more comments
0
I want to compute dynamic conditional correlation(dcc) mean matrix at all time.
Rho is each day matrix.
but i want to make a mean matrix all day (not each day)
this is DCC-garch model.
library(rugarch)
library(rmgarch)
library(xts)
stockdata<-read.zoo("C:\Users\Taehee Cha\Desktop\\data\EUCall.csv",
header=TRUE,
sep=",",
format = "%Y-%m-%d",
nrow=4433)
stock_xts<-as.xts(stockdata,dateFormat='POSIXct')
DKOSPI200 <-diff(log(stock_xts$KOSPI200))*100
DDAX30 <-diff(log(stock_xts$DAX30))*100
DSNP500 <-diff(log(stock_xts$SNP500))*100
DFTSE100 <-diff(log(stock_xts$FTSE100))*100
...
data2<-data.frame(DKOSPI200,DDAX30,DSNP500,DFTSE100,DEUROSTOXX50,DFTSEMIB,DNIKKEI225,DSNPTSX,DCAC40,DJSE40,
DRTS,DIPC,DBOVESPA,DTadawul,DMERV,DSENSEX,DJSX,DSSE,DXU100,DSNPASX,
DATHEX,DAEX,DOBX,DSNPNZ50,DTAIEX,DOMXC20,DKLCI,DBEL20,DOMXS30,DSMI,
DIBEX,DSTI,DADX,DISEQ,DATX,DTA35,DEGX30,DPX50,DIPSA,DQE,
DIGBC,DSET,DKarachi100,DSNPBVL,DPSI20,DWIG20,DOMXH25,DPSEI,DBUX,DHANGSENG)
Univarate GARCH specification
gjrGARCH.spec <-ugarchspec(variance.model=list(model="gjrGARCH",garchOrder=c(1,1)),mean.model=list(armaOrder=c(1,0)))
Multivarate GARCH specification
dcc.gjrGARCH.spec=dccspec(uspec=multispec(replicate(50,gjrGARCH.spec)),
dccOrder=c(1,1),
distribution="mvnorm")
OUTCOME=dccfit(dcc.gjrGARCH.spec, data=data2)
Fit<-fitted(OUTCOME)
Sigma<-sigma(OUTCOME)
Rho<-rcor(OUTCOME)
dim(Rho)
>50 50 4432
I tried this, but I failed.
dccmean<-apply(Rho, c(1:4432), mean)
Error message:
Error in if (d2 == 0L) { : missing value where TRUE/FALSE needed
please help me....
> dput(head(data2))
structure(list(KOSPI200 = c(-0.64107155376405, -2.63428514277591,
-3.02361881202007, -0.348129159251176, -0.8463497185911, 0.933495693605124
), DAX30 = c(-0.275158289647415, -2.31165589473132, 0.132288230298805,
-0.916302412003311, -0.249954511741102, 1.5067409708557), SNP500 = c(0,
-1.23978129442266, -2.37787312356224, 0.68553903957973, -1.45026278352685,
-0.113477591886735), FTSE100 = c(-0.912643889420117, -1.27612498082748,
-0.189622000351441, -0.0175554735125871, -1.40042215908522, 1.65029716900129
), EUROSTOXX50 = c(-0.693995680230763, -2.63873467285407, 0.0340923169277474,
-1.10692637764913, -1.45688992650648, 0.90690109636018), FTSEMIB = c(-0.207307997135331,
-2.20987523065315, 0.11929602916414, -0.591164923299203, -1.23334692081265,
0.0674451667508791), NIKKEI225 = c(-0.172132904979705, -2.41825620786038,
-0.541031623946608, 0.494946220458736, -2.43002026761108, 3.30050037277818
), SNPTSX = c(-0.228827286223954, -0.618158165738869, -1.163192751949,
0.611234081963197, -1.07887096999253, 0.15982056970163), CAC40 = c(-0.996225333005363,
-2.45923020374033, 0.558708030675348, -1.07932737047562, -1.18770661796788,
0.946736097241008), JSE40 = c(-1.24801019778307, -0.660388491185593,
-0.378077731086712, 1.12913917165454, -0.270357667812782, 0.925230160391344
), RTS = c(1.69252595201295, -2.47912051247043, -1.68278329224893,
-0.628193976078784, -5.81832854668214, 2.33324601133127), IPC = c(0.410660821053099,
-0.793221688816637, -1.46058560736098, -0.0995162816563422, 0.0582618177329408,
-2.24304020680233), BOVESPA = c(-2.08399544316435, -0.0640501036023977,
-1.00884481719454, 0, -2.45326225130107, 1.76775969319749), Tadawul = c(-0.0751612871260576,
1.06988441714364, 0.467558379080923, 0.015629948658713, -0.479468927554549,
0.115645625170213), MERV = c(-0.812834284218145, -3.48526114996641,
-0.789176542098158, 0, -6.3347627637631, -2.25802417775345),
SENSEX = c(0.173466860804083, -0.357822108056638, -0.45387164272519,
1.1318914393021, 1.4301129114795, 2.24172363852979), JSX = c(0.464645515331874,
0.433624214120076, 0.382746462253802, 0.245017602482989,
0.417626097951018, 0.919117215344212), SSE = c(-0.9304947624722,
-0.512019911931727, -0.0399062163143782, 0.923519675548068,
-0.965701174169897, -0.149922817153048), XU100 = c(0.83997183599358,
-9.44220433432204, -1.19486088286003, -5.93037167728525,
-8.13019316543659, 4.39805147087551), SNPASX = c(-1.52481837941529,
-0.710076219124112, -0.355441763724151, 0.43889183264465,
0.632546988595983, 0.431277069387725), ATHEX = c(0.217251999604962,
-0.113093185749946, -4.08702446400842, -1.49759637062132,
-2.89449541976028, 2.84821759239637), AEX = c(-0.302724751872496,
-1.93350674725812, -0.334531789971226, -0.27844233175518,
-1.47467944242914, 0.59320521917563), OBX = c(-0.633345799178109,
-0.0872437271016935, -0.0686020794624653, -0.751459482064121,
-0.314782430663918, -0.138818800687446), SNPNZ50 = c(-0.589289243578772,
-0.212470628567818, -1.09525597597484, 1.56062961309287,
-0.594970797797778, 0.308439154148132), TAIEX = c(-0.634186259073921,
-0.0465155309724352, -1.06170058328026, -0.875355087660168,
-1.4930992055346, 1.85698166429091), OMXC20 = c(0.0415607672345608,
-0.892547743122307, 0.895744009882993, 0.00639222705407505,
-0.515886239547392, -0.744864387047794), KLCI = c(3.12710622798287,
1.55475618644338, 0.141888091655584, -0.2344629562125, -1.32130772048118,
-1.3324408754646), BEL20 = c(0.916239489510673, -0.838871120292239,
-0.349848101836958, 0.131119279926573, -0.220949965581685,
0.925072128183135), OMXS30 = c(-2.30694346428235, -3.59314374436401,
-0.132526843920378, -0.26558175544098, -0.700219536449254,
2.21356560948696), SMI = c(-0.923178651961543, -1.9888683347407,
0.190440901601185, -1.31581319814948, -1.24166996356809,
1.74938111396603), IBEX = c(-1.10228247337272, -3.30519689438287,
0.28541077977593, -0.719194686241131, -2.37890150982238,
-1.20979032592885), STI = c(-0.376825693193794, -1.56959227075815,
-0.209405887533087, 1.59189359203387, -0.998471722830718,
0.524545937488519), ADX = c(0, 0.234110707042312, -0.140988509294804,
-0.107833632972643, -0.00392341494084292, 0), ISEQ = c(-0.497210204416199,
-1.28827940816549, 1.05427460869301, 0.691923594974142, -1.2985333059083,
1.05885040639215), ATX = c(0.196176688098504, -0.397720264421864,
0.765032409498989, 0.634860192671294, -0.718109388684507,
0.288191756274081), TA35 = c(-0.467643907976623, -1.6933214269244,
0.638360404963567, 1.66873087937374, -1.03207784150818, 1.98476257832283
), EGX30 = c(-1.60808620054533, 0.486603179063838, 0.042060989053283,
-0.582335360174024, -1.05485347621963, 0.329916835288824),
PX50 = c(0, 0, -1.53717800478548, -0.567132576686191, -1.79645549752987,
0.100654261140143), IPSA = c(0.561439712306022, 0.849792667039129,
-0.327031029818503, -0.154168073702365, -0.737696755949457,
-0.476817106576277), QE = c(0.124155575561335, -0.299696872832733,
-0.087886339332055, 0.0366286953290995, 0.109805655043083,
0.0585137524009127), IGBC = c(0.151884596926966, -0.461362987666014,
1.12811837108895, 0.0931901841028981, 0.149517561508272,
0.312176099410877), SET = c(-0.475964725298805, 0, -0.126280143061397,
-0.243770852799319, -3.47030045650181, 0.752026997121558),
Karachi100 = c(-1.2595250361283, -1.09859841657665, -0.467295948347779,
-0.176282035250352, 1.06144685237481, 0.614077017080827),
SNPBVL = c(-0.0916272845215893, -0.488603970907153, -0.635609686024718,
0.72544080956467, -1.05989054433602, -0.290056131898186),
PSI20 = c(-0.498150623441695, -2.4995090145449, -0.916173928749231,
0.134620833204835, -1.96674118284665, 0.125363501017972),
WIG20 = c(-0.186154209522993, 2.29090171954054, -1.21234613135197,
-2.35741884661973, -1.39537944100319, 4.04050146384076),
OMXH25 = c(-0.734161177012371, -3.2781107280087, -0.274240630336653,
0.164265778301331, -2.88555610228327, 0.0196123710402674),
PSEI = c(1.16491407781849, -0.379401344663943, 0.604503127264966,
-0.551543468404248, -0.542372265371061, 0.668217806598204
), BUX = c(0.745432319945749, -0.407296683745706, 1.4847908668413,
-1.73656177766137, -1.70838647119353, 0.642365839539494),
HANGSENG = c(-1.58777648289217, 0, -2.40414908704771, 0.182801734695737,
-1.47377260414583, 1.05050572830176)), row.names = c("2001-07-05",
"2001-07-06", "2001-07-09", "2001-07-10", "2001-07-11", "2001-07-12"
), class = "data.frame")
I think it will be more useful to solve my problem.
dim(Rho)
>50 50 4432
> dput(head(Rho))
c(1, 0.28274756492168, 0.366762864615763, 0.287187938929745,
0.279313675150249, 0.25099353597608)
> str(Rho)
num [1:50, 1:50, 1:4432] 1 0.283 0.367 0.287 0.279 ...
- attr(*, "dimnames")=List of 3
..$ : chr [1:50] "KOSPI200" "DAX30" "SNP500" "FTSE100" ...
..$ : chr [1:50] "KOSPI200" "DAX30" "SNP500" "FTSE100" ...
..$ : chr [1:4432] "2001-07-05" "2001-07-06" "2001-07-09" "2001-07-10" ...
My questions
#, , "2001-07-05"
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 1 5 9 13
#DAX30 2 6 10 14
#SNP500 3 7 11 15
#FTSE100 4 8 12 16
#, , "2001-07-06"
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 1 5 9 13
#DAX30 2 6 10 14
#SNP500 3 7 11 15
#FTSE100 4 8 12 16
##----->I want to this ((ex)sum)
#, ,
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 2 10 18 26
#DAX30 4 12 20 28
#SNP500 6 14 22 30
#FTSE100 8 16 24 32
r multidimensional-array apply mean correlation
asked Nov 20 at 13:24
차태희
62
1
Please specify the used libraries and providedata2.
– jay.sf
Nov 20 at 13:41
1
data2 is difference time data.
– 차태희
Nov 20 at 15:12
1
Can you post the output ofdput(data2), or if its too longdput(head(data2))into the question?
– jay.sf
Nov 20 at 15:14
I modified the edit.
– 차태희
Nov 20 at 15:31
1
Better. But we cannot reproduce"C:\Users\Taehee Cha\Desktop\\data\EUCall.csv". You should providestockdatatoo. Probably you should consider How to make a great reproducible example, thanks.
– jay.sf
Nov 20 at 15:47
|
show 3 more comments
0
0
0
I want to compute dynamic conditional correlation(dcc) mean matrix at all time.
Rho is each day matrix.
but i want to make a mean matrix all day (not each day)
this is DCC-garch model.
library(rugarch)
library(rmgarch)
library(xts)
stockdata<-read.zoo("C:\Users\Taehee Cha\Desktop\\data\EUCall.csv",
header=TRUE,
sep=",",
format = "%Y-%m-%d",
nrow=4433)
stock_xts<-as.xts(stockdata,dateFormat='POSIXct')
DKOSPI200 <-diff(log(stock_xts$KOSPI200))*100
DDAX30 <-diff(log(stock_xts$DAX30))*100
DSNP500 <-diff(log(stock_xts$SNP500))*100
DFTSE100 <-diff(log(stock_xts$FTSE100))*100
...
data2<-data.frame(DKOSPI200,DDAX30,DSNP500,DFTSE100,DEUROSTOXX50,DFTSEMIB,DNIKKEI225,DSNPTSX,DCAC40,DJSE40,
DRTS,DIPC,DBOVESPA,DTadawul,DMERV,DSENSEX,DJSX,DSSE,DXU100,DSNPASX,
DATHEX,DAEX,DOBX,DSNPNZ50,DTAIEX,DOMXC20,DKLCI,DBEL20,DOMXS30,DSMI,
DIBEX,DSTI,DADX,DISEQ,DATX,DTA35,DEGX30,DPX50,DIPSA,DQE,
DIGBC,DSET,DKarachi100,DSNPBVL,DPSI20,DWIG20,DOMXH25,DPSEI,DBUX,DHANGSENG)
Univarate GARCH specification
gjrGARCH.spec <-ugarchspec(variance.model=list(model="gjrGARCH",garchOrder=c(1,1)),mean.model=list(armaOrder=c(1,0)))
Multivarate GARCH specification
dcc.gjrGARCH.spec=dccspec(uspec=multispec(replicate(50,gjrGARCH.spec)),
dccOrder=c(1,1),
distribution="mvnorm")
OUTCOME=dccfit(dcc.gjrGARCH.spec, data=data2)
Fit<-fitted(OUTCOME)
Sigma<-sigma(OUTCOME)
Rho<-rcor(OUTCOME)
dim(Rho)
>50 50 4432
I tried this, but I failed.
dccmean<-apply(Rho, c(1:4432), mean)
Error message:
Error in if (d2 == 0L) { : missing value where TRUE/FALSE needed
please help me....
> dput(head(data2))
structure(list(KOSPI200 = c(-0.64107155376405, -2.63428514277591,
-3.02361881202007, -0.348129159251176, -0.8463497185911, 0.933495693605124
), DAX30 = c(-0.275158289647415, -2.31165589473132, 0.132288230298805,
-0.916302412003311, -0.249954511741102, 1.5067409708557), SNP500 = c(0,
-1.23978129442266, -2.37787312356224, 0.68553903957973, -1.45026278352685,
-0.113477591886735), FTSE100 = c(-0.912643889420117, -1.27612498082748,
-0.189622000351441, -0.0175554735125871, -1.40042215908522, 1.65029716900129
), EUROSTOXX50 = c(-0.693995680230763, -2.63873467285407, 0.0340923169277474,
-1.10692637764913, -1.45688992650648, 0.90690109636018), FTSEMIB = c(-0.207307997135331,
-2.20987523065315, 0.11929602916414, -0.591164923299203, -1.23334692081265,
0.0674451667508791), NIKKEI225 = c(-0.172132904979705, -2.41825620786038,
-0.541031623946608, 0.494946220458736, -2.43002026761108, 3.30050037277818
), SNPTSX = c(-0.228827286223954, -0.618158165738869, -1.163192751949,
0.611234081963197, -1.07887096999253, 0.15982056970163), CAC40 = c(-0.996225333005363,
-2.45923020374033, 0.558708030675348, -1.07932737047562, -1.18770661796788,
0.946736097241008), JSE40 = c(-1.24801019778307, -0.660388491185593,
-0.378077731086712, 1.12913917165454, -0.270357667812782, 0.925230160391344
), RTS = c(1.69252595201295, -2.47912051247043, -1.68278329224893,
-0.628193976078784, -5.81832854668214, 2.33324601133127), IPC = c(0.410660821053099,
-0.793221688816637, -1.46058560736098, -0.0995162816563422, 0.0582618177329408,
-2.24304020680233), BOVESPA = c(-2.08399544316435, -0.0640501036023977,
-1.00884481719454, 0, -2.45326225130107, 1.76775969319749), Tadawul = c(-0.0751612871260576,
1.06988441714364, 0.467558379080923, 0.015629948658713, -0.479468927554549,
0.115645625170213), MERV = c(-0.812834284218145, -3.48526114996641,
-0.789176542098158, 0, -6.3347627637631, -2.25802417775345),
SENSEX = c(0.173466860804083, -0.357822108056638, -0.45387164272519,
1.1318914393021, 1.4301129114795, 2.24172363852979), JSX = c(0.464645515331874,
0.433624214120076, 0.382746462253802, 0.245017602482989,
0.417626097951018, 0.919117215344212), SSE = c(-0.9304947624722,
-0.512019911931727, -0.0399062163143782, 0.923519675548068,
-0.965701174169897, -0.149922817153048), XU100 = c(0.83997183599358,
-9.44220433432204, -1.19486088286003, -5.93037167728525,
-8.13019316543659, 4.39805147087551), SNPASX = c(-1.52481837941529,
-0.710076219124112, -0.355441763724151, 0.43889183264465,
0.632546988595983, 0.431277069387725), ATHEX = c(0.217251999604962,
-0.113093185749946, -4.08702446400842, -1.49759637062132,
-2.89449541976028, 2.84821759239637), AEX = c(-0.302724751872496,
-1.93350674725812, -0.334531789971226, -0.27844233175518,
-1.47467944242914, 0.59320521917563), OBX = c(-0.633345799178109,
-0.0872437271016935, -0.0686020794624653, -0.751459482064121,
-0.314782430663918, -0.138818800687446), SNPNZ50 = c(-0.589289243578772,
-0.212470628567818, -1.09525597597484, 1.56062961309287,
-0.594970797797778, 0.308439154148132), TAIEX = c(-0.634186259073921,
-0.0465155309724352, -1.06170058328026, -0.875355087660168,
-1.4930992055346, 1.85698166429091), OMXC20 = c(0.0415607672345608,
-0.892547743122307, 0.895744009882993, 0.00639222705407505,
-0.515886239547392, -0.744864387047794), KLCI = c(3.12710622798287,
1.55475618644338, 0.141888091655584, -0.2344629562125, -1.32130772048118,
-1.3324408754646), BEL20 = c(0.916239489510673, -0.838871120292239,
-0.349848101836958, 0.131119279926573, -0.220949965581685,
0.925072128183135), OMXS30 = c(-2.30694346428235, -3.59314374436401,
-0.132526843920378, -0.26558175544098, -0.700219536449254,
2.21356560948696), SMI = c(-0.923178651961543, -1.9888683347407,
0.190440901601185, -1.31581319814948, -1.24166996356809,
1.74938111396603), IBEX = c(-1.10228247337272, -3.30519689438287,
0.28541077977593, -0.719194686241131, -2.37890150982238,
-1.20979032592885), STI = c(-0.376825693193794, -1.56959227075815,
-0.209405887533087, 1.59189359203387, -0.998471722830718,
0.524545937488519), ADX = c(0, 0.234110707042312, -0.140988509294804,
-0.107833632972643, -0.00392341494084292, 0), ISEQ = c(-0.497210204416199,
-1.28827940816549, 1.05427460869301, 0.691923594974142, -1.2985333059083,
1.05885040639215), ATX = c(0.196176688098504, -0.397720264421864,
0.765032409498989, 0.634860192671294, -0.718109388684507,
0.288191756274081), TA35 = c(-0.467643907976623, -1.6933214269244,
0.638360404963567, 1.66873087937374, -1.03207784150818, 1.98476257832283
), EGX30 = c(-1.60808620054533, 0.486603179063838, 0.042060989053283,
-0.582335360174024, -1.05485347621963, 0.329916835288824),
PX50 = c(0, 0, -1.53717800478548, -0.567132576686191, -1.79645549752987,
0.100654261140143), IPSA = c(0.561439712306022, 0.849792667039129,
-0.327031029818503, -0.154168073702365, -0.737696755949457,
-0.476817106576277), QE = c(0.124155575561335, -0.299696872832733,
-0.087886339332055, 0.0366286953290995, 0.109805655043083,
0.0585137524009127), IGBC = c(0.151884596926966, -0.461362987666014,
1.12811837108895, 0.0931901841028981, 0.149517561508272,
0.312176099410877), SET = c(-0.475964725298805, 0, -0.126280143061397,
-0.243770852799319, -3.47030045650181, 0.752026997121558),
Karachi100 = c(-1.2595250361283, -1.09859841657665, -0.467295948347779,
-0.176282035250352, 1.06144685237481, 0.614077017080827),
SNPBVL = c(-0.0916272845215893, -0.488603970907153, -0.635609686024718,
0.72544080956467, -1.05989054433602, -0.290056131898186),
PSI20 = c(-0.498150623441695, -2.4995090145449, -0.916173928749231,
0.134620833204835, -1.96674118284665, 0.125363501017972),
WIG20 = c(-0.186154209522993, 2.29090171954054, -1.21234613135197,
-2.35741884661973, -1.39537944100319, 4.04050146384076),
OMXH25 = c(-0.734161177012371, -3.2781107280087, -0.274240630336653,
0.164265778301331, -2.88555610228327, 0.0196123710402674),
PSEI = c(1.16491407781849, -0.379401344663943, 0.604503127264966,
-0.551543468404248, -0.542372265371061, 0.668217806598204
), BUX = c(0.745432319945749, -0.407296683745706, 1.4847908668413,
-1.73656177766137, -1.70838647119353, 0.642365839539494),
HANGSENG = c(-1.58777648289217, 0, -2.40414908704771, 0.182801734695737,
-1.47377260414583, 1.05050572830176)), row.names = c("2001-07-05",
"2001-07-06", "2001-07-09", "2001-07-10", "2001-07-11", "2001-07-12"
), class = "data.frame")
I think it will be more useful to solve my problem.
dim(Rho)
>50 50 4432
> dput(head(Rho))
c(1, 0.28274756492168, 0.366762864615763, 0.287187938929745,
0.279313675150249, 0.25099353597608)
> str(Rho)
num [1:50, 1:50, 1:4432] 1 0.283 0.367 0.287 0.279 ...
- attr(*, "dimnames")=List of 3
..$ : chr [1:50] "KOSPI200" "DAX30" "SNP500" "FTSE100" ...
..$ : chr [1:50] "KOSPI200" "DAX30" "SNP500" "FTSE100" ...
..$ : chr [1:4432] "2001-07-05" "2001-07-06" "2001-07-09" "2001-07-10" ...
My questions
#, , "2001-07-05"
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 1 5 9 13
#DAX30 2 6 10 14
#SNP500 3 7 11 15
#FTSE100 4 8 12 16
#, , "2001-07-06"
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 1 5 9 13
#DAX30 2 6 10 14
#SNP500 3 7 11 15
#FTSE100 4 8 12 16
##----->I want to this ((ex)sum)
#, ,
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 2 10 18 26
#DAX30 4 12 20 28
#SNP500 6 14 22 30
#FTSE100 8 16 24 32
r multidimensional-array apply mean correlation
asked Nov 20 at 13:24
차태희
62
I want to compute dynamic conditional correlation(dcc) mean matrix at all time.
Rho is each day matrix.
but i want to make a mean matrix all day (not each day)
this is DCC-garch model.
library(rugarch)
library(rmgarch)
library(xts)
stockdata<-read.zoo("C:\Users\Taehee Cha\Desktop\\data\EUCall.csv",
header=TRUE,
sep=",",
format = "%Y-%m-%d",
nrow=4433)
stock_xts<-as.xts(stockdata,dateFormat='POSIXct')
DKOSPI200 <-diff(log(stock_xts$KOSPI200))*100
DDAX30 <-diff(log(stock_xts$DAX30))*100
DSNP500 <-diff(log(stock_xts$SNP500))*100
DFTSE100 <-diff(log(stock_xts$FTSE100))*100
...
data2<-data.frame(DKOSPI200,DDAX30,DSNP500,DFTSE100,DEUROSTOXX50,DFTSEMIB,DNIKKEI225,DSNPTSX,DCAC40,DJSE40,
DRTS,DIPC,DBOVESPA,DTadawul,DMERV,DSENSEX,DJSX,DSSE,DXU100,DSNPASX,
DATHEX,DAEX,DOBX,DSNPNZ50,DTAIEX,DOMXC20,DKLCI,DBEL20,DOMXS30,DSMI,
DIBEX,DSTI,DADX,DISEQ,DATX,DTA35,DEGX30,DPX50,DIPSA,DQE,
DIGBC,DSET,DKarachi100,DSNPBVL,DPSI20,DWIG20,DOMXH25,DPSEI,DBUX,DHANGSENG)
Univarate GARCH specification
gjrGARCH.spec <-ugarchspec(variance.model=list(model="gjrGARCH",garchOrder=c(1,1)),mean.model=list(armaOrder=c(1,0)))
Multivarate GARCH specification
dcc.gjrGARCH.spec=dccspec(uspec=multispec(replicate(50,gjrGARCH.spec)),
dccOrder=c(1,1),
distribution="mvnorm")
OUTCOME=dccfit(dcc.gjrGARCH.spec, data=data2)
Fit<-fitted(OUTCOME)
Sigma<-sigma(OUTCOME)
Rho<-rcor(OUTCOME)
dim(Rho)
>50 50 4432
I tried this, but I failed.
dccmean<-apply(Rho, c(1:4432), mean)
Error message:
Error in if (d2 == 0L) { : missing value where TRUE/FALSE needed
please help me....
> dput(head(data2))
structure(list(KOSPI200 = c(-0.64107155376405, -2.63428514277591,
-3.02361881202007, -0.348129159251176, -0.8463497185911, 0.933495693605124
), DAX30 = c(-0.275158289647415, -2.31165589473132, 0.132288230298805,
-0.916302412003311, -0.249954511741102, 1.5067409708557), SNP500 = c(0,
-1.23978129442266, -2.37787312356224, 0.68553903957973, -1.45026278352685,
-0.113477591886735), FTSE100 = c(-0.912643889420117, -1.27612498082748,
-0.189622000351441, -0.0175554735125871, -1.40042215908522, 1.65029716900129
), EUROSTOXX50 = c(-0.693995680230763, -2.63873467285407, 0.0340923169277474,
-1.10692637764913, -1.45688992650648, 0.90690109636018), FTSEMIB = c(-0.207307997135331,
-2.20987523065315, 0.11929602916414, -0.591164923299203, -1.23334692081265,
0.0674451667508791), NIKKEI225 = c(-0.172132904979705, -2.41825620786038,
-0.541031623946608, 0.494946220458736, -2.43002026761108, 3.30050037277818
), SNPTSX = c(-0.228827286223954, -0.618158165738869, -1.163192751949,
0.611234081963197, -1.07887096999253, 0.15982056970163), CAC40 = c(-0.996225333005363,
-2.45923020374033, 0.558708030675348, -1.07932737047562, -1.18770661796788,
0.946736097241008), JSE40 = c(-1.24801019778307, -0.660388491185593,
-0.378077731086712, 1.12913917165454, -0.270357667812782, 0.925230160391344
), RTS = c(1.69252595201295, -2.47912051247043, -1.68278329224893,
-0.628193976078784, -5.81832854668214, 2.33324601133127), IPC = c(0.410660821053099,
-0.793221688816637, -1.46058560736098, -0.0995162816563422, 0.0582618177329408,
-2.24304020680233), BOVESPA = c(-2.08399544316435, -0.0640501036023977,
-1.00884481719454, 0, -2.45326225130107, 1.76775969319749), Tadawul = c(-0.0751612871260576,
1.06988441714364, 0.467558379080923, 0.015629948658713, -0.479468927554549,
0.115645625170213), MERV = c(-0.812834284218145, -3.48526114996641,
-0.789176542098158, 0, -6.3347627637631, -2.25802417775345),
SENSEX = c(0.173466860804083, -0.357822108056638, -0.45387164272519,
1.1318914393021, 1.4301129114795, 2.24172363852979), JSX = c(0.464645515331874,
0.433624214120076, 0.382746462253802, 0.245017602482989,
0.417626097951018, 0.919117215344212), SSE = c(-0.9304947624722,
-0.512019911931727, -0.0399062163143782, 0.923519675548068,
-0.965701174169897, -0.149922817153048), XU100 = c(0.83997183599358,
-9.44220433432204, -1.19486088286003, -5.93037167728525,
-8.13019316543659, 4.39805147087551), SNPASX = c(-1.52481837941529,
-0.710076219124112, -0.355441763724151, 0.43889183264465,
0.632546988595983, 0.431277069387725), ATHEX = c(0.217251999604962,
-0.113093185749946, -4.08702446400842, -1.49759637062132,
-2.89449541976028, 2.84821759239637), AEX = c(-0.302724751872496,
-1.93350674725812, -0.334531789971226, -0.27844233175518,
-1.47467944242914, 0.59320521917563), OBX = c(-0.633345799178109,
-0.0872437271016935, -0.0686020794624653, -0.751459482064121,
-0.314782430663918, -0.138818800687446), SNPNZ50 = c(-0.589289243578772,
-0.212470628567818, -1.09525597597484, 1.56062961309287,
-0.594970797797778, 0.308439154148132), TAIEX = c(-0.634186259073921,
-0.0465155309724352, -1.06170058328026, -0.875355087660168,
-1.4930992055346, 1.85698166429091), OMXC20 = c(0.0415607672345608,
-0.892547743122307, 0.895744009882993, 0.00639222705407505,
-0.515886239547392, -0.744864387047794), KLCI = c(3.12710622798287,
1.55475618644338, 0.141888091655584, -0.2344629562125, -1.32130772048118,
-1.3324408754646), BEL20 = c(0.916239489510673, -0.838871120292239,
-0.349848101836958, 0.131119279926573, -0.220949965581685,
0.925072128183135), OMXS30 = c(-2.30694346428235, -3.59314374436401,
-0.132526843920378, -0.26558175544098, -0.700219536449254,
2.21356560948696), SMI = c(-0.923178651961543, -1.9888683347407,
0.190440901601185, -1.31581319814948, -1.24166996356809,
1.74938111396603), IBEX = c(-1.10228247337272, -3.30519689438287,
0.28541077977593, -0.719194686241131, -2.37890150982238,
-1.20979032592885), STI = c(-0.376825693193794, -1.56959227075815,
-0.209405887533087, 1.59189359203387, -0.998471722830718,
0.524545937488519), ADX = c(0, 0.234110707042312, -0.140988509294804,
-0.107833632972643, -0.00392341494084292, 0), ISEQ = c(-0.497210204416199,
-1.28827940816549, 1.05427460869301, 0.691923594974142, -1.2985333059083,
1.05885040639215), ATX = c(0.196176688098504, -0.397720264421864,
0.765032409498989, 0.634860192671294, -0.718109388684507,
0.288191756274081), TA35 = c(-0.467643907976623, -1.6933214269244,
0.638360404963567, 1.66873087937374, -1.03207784150818, 1.98476257832283
), EGX30 = c(-1.60808620054533, 0.486603179063838, 0.042060989053283,
-0.582335360174024, -1.05485347621963, 0.329916835288824),
PX50 = c(0, 0, -1.53717800478548, -0.567132576686191, -1.79645549752987,
0.100654261140143), IPSA = c(0.561439712306022, 0.849792667039129,
-0.327031029818503, -0.154168073702365, -0.737696755949457,
-0.476817106576277), QE = c(0.124155575561335, -0.299696872832733,
-0.087886339332055, 0.0366286953290995, 0.109805655043083,
0.0585137524009127), IGBC = c(0.151884596926966, -0.461362987666014,
1.12811837108895, 0.0931901841028981, 0.149517561508272,
0.312176099410877), SET = c(-0.475964725298805, 0, -0.126280143061397,
-0.243770852799319, -3.47030045650181, 0.752026997121558),
Karachi100 = c(-1.2595250361283, -1.09859841657665, -0.467295948347779,
-0.176282035250352, 1.06144685237481, 0.614077017080827),
SNPBVL = c(-0.0916272845215893, -0.488603970907153, -0.635609686024718,
0.72544080956467, -1.05989054433602, -0.290056131898186),
PSI20 = c(-0.498150623441695, -2.4995090145449, -0.916173928749231,
0.134620833204835, -1.96674118284665, 0.125363501017972),
WIG20 = c(-0.186154209522993, 2.29090171954054, -1.21234613135197,
-2.35741884661973, -1.39537944100319, 4.04050146384076),
OMXH25 = c(-0.734161177012371, -3.2781107280087, -0.274240630336653,
0.164265778301331, -2.88555610228327, 0.0196123710402674),
PSEI = c(1.16491407781849, -0.379401344663943, 0.604503127264966,
-0.551543468404248, -0.542372265371061, 0.668217806598204
), BUX = c(0.745432319945749, -0.407296683745706, 1.4847908668413,
-1.73656177766137, -1.70838647119353, 0.642365839539494),
HANGSENG = c(-1.58777648289217, 0, -2.40414908704771, 0.182801734695737,
-1.47377260414583, 1.05050572830176)), row.names = c("2001-07-05",
"2001-07-06", "2001-07-09", "2001-07-10", "2001-07-11", "2001-07-12"
), class = "data.frame")
I think it will be more useful to solve my problem.
dim(Rho)
>50 50 4432
> dput(head(Rho))
c(1, 0.28274756492168, 0.366762864615763, 0.287187938929745,
0.279313675150249, 0.25099353597608)
> str(Rho)
num [1:50, 1:50, 1:4432] 1 0.283 0.367 0.287 0.279 ...
- attr(*, "dimnames")=List of 3
..$ : chr [1:50] "KOSPI200" "DAX30" "SNP500" "FTSE100" ...
..$ : chr [1:50] "KOSPI200" "DAX30" "SNP500" "FTSE100" ...
..$ : chr [1:4432] "2001-07-05" "2001-07-06" "2001-07-09" "2001-07-10" ...
My questions
#, , "2001-07-05"
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 1 5 9 13
#DAX30 2 6 10 14
#SNP500 3 7 11 15
#FTSE100 4 8 12 16
#, , "2001-07-06"
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 1 5 9 13
#DAX30 2 6 10 14
#SNP500 3 7 11 15
#FTSE100 4 8 12 16
##----->I want to this ((ex)sum)
#, ,
# KOSPI200 DAX30 SNP500 FTSE100
#KOSPI200 2 10 18 26
#DAX30 4 12 20 28
#SNP500 6 14 22 30
#FTSE100 8 16 24 32
r multidimensional-array apply mean correlation
r multidimensional-array apply mean correlation
asked Nov 20 at 13:24
차태희
62
asked Nov 20 at 13:24
차태희
62
edited Nov 21 at 7:59
asked Nov 20 at 13:24
차태희
62
asked Nov 20 at 13:24
차태희
62
asked Nov 20 at 13:24
차태희
62
62
1
Please specify the used libraries and providedata2.
– jay.sf
Nov 20 at 13:41
1
data2 is difference time data.
– 차태희
Nov 20 at 15:12
1
Can you post the output ofdput(data2), or if its too longdput(head(data2))into the question?
– jay.sf
Nov 20 at 15:14
I modified the edit.
– 차태희
Nov 20 at 15:31
1
Better. But we cannot reproduce"C:\Users\Taehee Cha\Desktop\\data\EUCall.csv". You should providestockdatatoo. Probably you should consider How to make a great reproducible example, thanks.
– jay.sf
Nov 20 at 15:47
|
show 3 more comments
1
Please specify the used libraries and providedata2.
– jay.sf
Nov 20 at 13:41
1
data2 is difference time data.
– 차태희
Nov 20 at 15:12
1
Can you post the output ofdput(data2), or if its too longdput(head(data2))into the question?
– jay.sf
Nov 20 at 15:14
I modified the edit.
– 차태희
Nov 20 at 15:31
1
Better. But we cannot reproduce"C:\Users\Taehee Cha\Desktop\\data\EUCall.csv". You should providestockdatatoo. Probably you should consider How to make a great reproducible example, thanks.
– jay.sf
Nov 20 at 15:47
1
1
Please specify the used libraries and provide
data2.– jay.sf
Nov 20 at 13:41
Please specify the used libraries and provide
data2.– jay.sf
Nov 20 at 13:41
1
1
data2 is difference time data.
– 차태희
Nov 20 at 15:12
data2 is difference time data.
– 차태희
Nov 20 at 15:12
1
1
Can you post the output of
dput(data2), or if its too long dput(head(data2)) into the question?– jay.sf
Nov 20 at 15:14
Can you post the output of
dput(data2), or if its too long dput(head(data2)) into the question?– jay.sf
Nov 20 at 15:14
I modified the edit.
– 차태희
Nov 20 at 15:31
I modified the edit.
– 차태희
Nov 20 at 15:31
1
1
Better. But we cannot reproduce
"C:\Users\Taehee Cha\Desktop\\data\EUCall.csv". You should provide stockdata too. Probably you should consider How to make a great reproducible example, thanks.– jay.sf
Nov 20 at 15:47
Better. But we cannot reproduce
"C:\Users\Taehee Cha\Desktop\\data\EUCall.csv". You should provide stockdata too. Probably you should consider How to make a great reproducible example, thanks.– jay.sf
Nov 20 at 15:47
|
show 3 more comments
1 Answer
1
active
oldest
votes
1
The error of your code is in the MARGIN of your apply call. Do not use c(1:4412), use the actual margins which are the first and second dimension (hence c(1,2))
In the last example of your question:
day1 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
day2 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
Rho <- abind::abind(day1=day1,day2=day2, along = 3)
apply(Rho, c(1,2), sum)
A B C D
a 2 10 18 26
b 4 12 20 28
c 6 14 22 30
d 8 16 24 32
gives the wanted output.
answered Nov 21 at 18:13
Bastien
1,391720
add a comment |
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1 Answer
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1 Answer
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oldest
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active
oldest
votes
active
oldest
votes
1
The error of your code is in the MARGIN of your apply call. Do not use c(1:4412), use the actual margins which are the first and second dimension (hence c(1,2))
In the last example of your question:
day1 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
day2 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
Rho <- abind::abind(day1=day1,day2=day2, along = 3)
apply(Rho, c(1,2), sum)
A B C D
a 2 10 18 26
b 4 12 20 28
c 6 14 22 30
d 8 16 24 32
gives the wanted output.
answered Nov 21 at 18:13
Bastien
1,391720
add a comment |
1
The error of your code is in the MARGIN of your apply call. Do not use c(1:4412), use the actual margins which are the first and second dimension (hence c(1,2))
In the last example of your question:
day1 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
day2 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
Rho <- abind::abind(day1=day1,day2=day2, along = 3)
apply(Rho, c(1,2), sum)
A B C D
a 2 10 18 26
b 4 12 20 28
c 6 14 22 30
d 8 16 24 32
gives the wanted output.
answered Nov 21 at 18:13
Bastien
1,391720
add a comment |
1
1
1
The error of your code is in the MARGIN of your apply call. Do not use c(1:4412), use the actual margins which are the first and second dimension (hence c(1,2))
In the last example of your question:
day1 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
day2 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
Rho <- abind::abind(day1=day1,day2=day2, along = 3)
apply(Rho, c(1,2), sum)
A B C D
a 2 10 18 26
b 4 12 20 28
c 6 14 22 30
d 8 16 24 32
gives the wanted output.
answered Nov 21 at 18:13
Bastien
1,391720
The error of your code is in the MARGIN of your apply call. Do not use c(1:4412), use the actual margins which are the first and second dimension (hence c(1,2))
In the last example of your question:
day1 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
day2 <- matrix(1:16, 4, 4, dimnames = list(letters[1:4], LETTERS[1:4]))
Rho <- abind::abind(day1=day1,day2=day2, along = 3)
apply(Rho, c(1,2), sum)
A B C D
a 2 10 18 26
b 4 12 20 28
c 6 14 22 30
d 8 16 24 32
gives the wanted output.
answered Nov 21 at 18:13
Bastien
1,391720
answered Nov 21 at 18:13
Bastien
1,391720
answered Nov 21 at 18:13
Bastien
1,391720
answered Nov 21 at 18:13
Bastien
1,391720
1,391720
add a comment |
add a comment |
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1
Please specify the used libraries and provide
data2.– jay.sf
Nov 20 at 13:41
1
data2 is difference time data.
– 차태희
Nov 20 at 15:12
1
Can you post the output of
dput(data2), or if its too longdput(head(data2))into the question?– jay.sf
Nov 20 at 15:14
I modified the edit.
– 차태희
Nov 20 at 15:31
1
Better. But we cannot reproduce
"C:\Users\Taehee Cha\Desktop\\data\EUCall.csv". You should providestockdatatoo. Probably you should consider How to make a great reproducible example, thanks.– jay.sf
Nov 20 at 15:47