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Data:
-121501068376068.00 -0.161371254936967 0.0811524749725976 0.22659613938869 -0.16950119402658 -0.838993029294507 495786172848762.00 202169535503521.00 -48597034775381.00 344571492862308.00 -149170257466958.00 -123285862634735.00 -134370209564317.00 -149853980290352.00 844403883653735.00 776617191146284.00 151627681894306.00 129010036056204.00 -47147788442654.00 666885660135864.00 -202873981847779.00 -185665916727225.00 958024031985623.00 658583969572915.00 0.0316313537438901 113142775555447.00 12907392606119.00 285755288162555.00 -591801314983149.00 124860059602398.00 182408288799769.00 -558098403815903.00 -294181160162329.00 -852946272794134.00 -126608461609643.00 -81295021323577.00 -551030919689403.00 346554744303629.00 875328179766785.00 177072937304368.00 -20335040140385.00 322072173815324.00 171404412590385.00 535455892630974.00 603094579425778.00 -71939443559736.00 -198323721913934.00 -27737249773661.00 908019054774918.00 0.30569655593915 398543190734553.00 -339994987865782.00 0.772482627799803 201465220794604.00 160135867202347.00 103316306357328.00 897956173029057.00 260860741044216.00 -918379332670324.00 -964323059739233.00 -120330635118287.00 0.620518717410178 121349351619224.00 -493538212672495.00 -300166082229109.00 206710132097827.00 373445689598034.00 690695418093642.00 187612950743249.00 -972522703581288.00 -130420502338819.00 185149028580797.00 652543210418575.00 -382608131701302.00 -585064935079504.00 693890366690242.00 256166600951984.00 0.0905660301677216 -255772844604658.00 -163490319593022.00 156798078573283.00 424905634153647.00 -357918651748452.00 303311110493701.00 0.779654053501886 -0.513216446520588 110899733630286.00 349269911458272.00 0.258979039116213 376684700754228.00 -327557815105264.00 -0.189151109370698 -267091398880646.00 -0.282615724948684 -542237946427214.00 -55259728453525.00 0.720522935862363 -5192366394358.00 -132756276391527.00 0.811872895074004 -102236393682631.00 -472064030826415.00 397812326516453.00 608838195158165.00 667973671434819.00 10079128054835.00 338757529238939.00 927158256758933.00 0.380029862819569 124504922137227.00 -360772425066438.00 -373662995945442.00 -0.477591136245735 250264516173829.00 173999692963309.00 -543432204360964.00 -340920932864201.00 -414812885339785.00 -490873899101585.00 -785382899831731.00 -3567390945154.00 532433018994224.00 -3562902298986.00 0.317062708099002 -661557124521009.00 -192175123655812.00 705096882769004.00 -624088451587878.00 770345625057637.00 -319513117957479.00 117026984027629.00 -149572030461012.00 124539440855196.00 70030776194085.00 -746509536331014.00 -939152326155325.00 408622110583212.00 840087286777069.00 0.0657144923152089 632884805522616.00 -765134956674507.00
Sample Range:
(leave blank to include all observations)
From:
To:
Number of time lags
12
Default
5
6
7
8
9
10
11
12
24
36
48
60
Box-Cox transformation parameter (Lambda)
Triple
1
-2.0
-1.9
-1.8
-1.7
-1.6
-1.5
-1.4
-1.3
-1.2
-1.1
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
Degree of non-seasonal differencing (d)
additive
0
1
2
Degree of seasonal differencing (D)
0
1
2
Seasonality
12
1
2
3
4
6
12
CI type
White Noise
MA
Confidence Interval
Use logarithms with this base
(overrules the Box-Cox lambda parameter)
(?)
Chart options
R Code
if (par1 == 'Default') { par1 = 10*log10(length(x)) } else { par1 <- as.numeric(par1) } par2 <- as.numeric(par2) par3 <- as.numeric(par3) par4 <- as.numeric(par4) par5 <- as.numeric(par5) if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma' par7 <- as.numeric(par7) if (par8 != '') par8 <- as.numeric(par8) ox <- x if (par8 == '') { if (par2 == 0) { x <- log(x) } else { x <- (x ^ par2 - 1) / par2 } } else { x <- log(x,base=par8) } if (par3 > 0) x <- diff(x,lag=1,difference=par3) if (par4 > 0) x <- diff(x,lag=par5,difference=par4) bitmap(file='picts.png') op <- par(mfrow=c(2,1)) plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value') if (par8=='') { mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='') mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='') } else { mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='') mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='') } plot(x,type='l', main=mytitle,xlab='time',ylab='value') par(op) dev.off() bitmap(file='pic1.png') racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub) dev.off() bitmap(file='pic2.png') rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub) dev.off() (myacf <- c(racf$acf)) (mypacf <- c(rpacf$acf)) lengthx <- length(x) sqrtn <- sqrt(lengthx) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Autocorrelation Function',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Time lag k',header=TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,'P-value',header=TRUE) a<-table.row.end(a) for (i in 2:(par1+1)) { a<-table.row.start(a) a<-table.element(a,i-1,header=TRUE) a<-table.element(a,round(myacf[i],6)) mytstat <- myacf[i]*sqrtn a<-table.element(a,round(mytstat,4)) a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Partial Autocorrelation Function',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Time lag k',header=TRUE) a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE) a<-table.element(a,'T-STAT',header=TRUE) a<-table.element(a,'P-value',header=TRUE) a<-table.row.end(a) for (i in 1:par1) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,round(mypacf[i],6)) mytstat <- mypacf[i]*sqrtn a<-table.element(a,round(mytstat,4)) a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')
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Raw Input
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Raw Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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