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Data:
'?2000M1;46' '2000M2;52' '2000M3;58' '2000M4;54' '2000M5;64' '2000M6;58' '2000M7;57' '2000M8;56' '2000M9;56' '2000M10;66' '2000M11;58' '2000M12;53' '2001M1;53' '2001M2;54' '2001M3;59' '2001M4;57' '2001M5;61' '2001M6;60' '2001M7;60' '2001M8;58' '2001M9;56' '2001M10;63' '2001M11;53' '2001M12;63' '2002M1;55' '2002M2;54' '2002M3;64' '2002M4;60' '2002M5;63' '2002M6;69' '2002M7;58' '2002M8;52' '2002M9;66' '2002M10;72' '2002M11;68' '2002M12;70' '2003M1;56' '2003M2;62' '2003M3;66' '2003M4;69' '2003M5;63' '2003M6;73' '2003M7;64' '2003M8;53' '2003M9;72' '2003M10;80' '2003M11;69' '2003M12;72' '2004M1;66' '2004M2;72' '2004M3;88' '2004M4;88' '2004M5;73' '2004M6;86' '2004M7;70' '2004M8;71' '2004M9;90' '2004M10;85' '2004M11;84' '2004M12;81' '2005M1;70' '2005M2;65' '2005M3;86' '2005M4;76' '2005M5;79' '2005M6;85' '2005M7;75' '2005M8;69' '2005M9;85' '2005M10;75' '2005M11;77' '2005M12;68' '2006M1;68' '2006M2;65' '2006M3;73' '2006M4;67' '2006M5;76' '2006M6;85' '2006M7;71' '2006M8;57' '2006M9;75' '2006M10;78' '2006M11;75' '2006M12;67' '2007M1;74' '2007M2;66' '2007M3;74' '2007M4;69' '2007M5;76' '2007M6;82' '2007M7;82' '2007M8;60' '2007M9;71' '2007M10;81' '2007M11;74' '2007M12;61' '2008M1;83' '2008M2;85' '2008M3;91' '2008M4;91' '2008M5;86' '2008M6;96' '2008M7;81' '2008M8;70' '2008M9;98' '2008M10;94' '2008M11;84' '2008M12;92' '2009M1;81' '2009M2;75' '2009M3;86' '2009M4;87' '2009M5;87' '2009M6;103' '2009M7;96' '2009M8;77' '2009M9;106' '2009M10;95' '2009M11;95' '2009M12;86' '2010M1;89' '2010M2;81' '2010M3;98' '2010M4;92' '2010M5;83' '2010M6;121' '2010M7;103' '2010M8;87' '2010M9;118' '2010M10;109' '2010M11;112' '2010M12;100' '2011M1;111' '2011M2;102' '2011M3;122' '2011M4;124' '2011M5;120' '2011M6;118' '2011M7;108' '2011M8;100' '2011M9;124' '2011M10;103' '2011M11;115' '2011M12;112' '2012M1;101' '2012M2;111' '2012M3;114' '2012M4;112' '2012M5;107' '2012M6;136' '2012M7;107' '2012M8;94' '2012M9;110' '2012M10;126' '2012M11;127' '2012M12;109' '2013M1;87' '2013M2;90' '2013M3;94' '2013M4;103' '2013M5;103' '2013M6;105' '2013M7;103' '2013M8;79' '2013M9;105' '2013M10;113' '2013M11;87' '2013M12;110' '2014M1;90' '2014M2;108' '2014M3;105' '2014M4;113' '2014M5;100' '2014M6;110' '2014M7;114' '2014M8;88' '2014M9;117' '2014M10;127' '2014M11;107' '2014M12;102' '2015M1;100' '2015M2;108' '2015M3;114' '2015M4;94' '2015M5;92' '2015M6;115' '2015M7;102' '2015M8;86' '2015M9;112' '2015M10;112' '2015M11;109' '2015M12;105' '2016M1;115' '2016M2;126' '2016M3;112' '2016M4;112' '2016M5;106' '2016M6;90' '2016M7;75' '2016M8;78' '2016M9;101' '2016M10;93' '2016M11;100' '2016M12;89' '2017M1;97' '2017M2;121' '2017M3;108' '2017M4;92' '2017M5;113' '2017M6;112' '2017M7;98'
Sample Range:
(leave blank to include all observations)
From:
To:
Number of time lags
48
Default
5
6
7
8
9
10
11
12
24
36
48
60
Box-Cox transformation parameter (Lambda)
1
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)
0
0
1
2
Degree of seasonal differencing (D)
0
0
1
2
Seasonality
12
12
1
2
3
4
6
12
CI type
White Noise
White Noise
MA
Confidence Interval
Use logarithms with this base
(overrules the Box-Cox lambda parameter)
(?)
Chart options
R Code
par8 <- '' par7 <- '0.95' par6 <- 'White Noise' par5 <- '12' par4 <- '0' par3 <- '0' par2 <- '1' par1 <- '48' 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) x <- na.omit(x) 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,'ACF(k)',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,'PACF(k)',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 Output
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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