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Totaal en machines (D=1)

R Software Module: rwasp_cross.wasp (opens new window with default values)
Title produced by software: Cross Correlation Function
Date of computation: Sun, 25 Nov 2007 08:19:15 -0700
 
Cite this page as follows:
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2007/Nov/25/t1196003613xrhrbra93ptsekw.htm/, Retrieved Sun, 25 Nov 2007 16:13:33 +0100
 
User-defined keywords:
 
Dataseries X:
» Textbox « » Textfile « » CSV «
112.6 113.8 107.8 103.2 103.3 101.2 107.7 110.4 101.9 115.9 89.9 88.6 117.2 123.9 100 103.6 94.1 98.7 119.5 112.7 104.4 124.7 89.1 97 121.6 118.8 114 111.5 97.2 102.5 113.4 109.8 104.9 126.1 80 96.8 117.2 112.3 117.3 111.1 102.2 104.3 122.9 107.6 121.3 131.5 89 104.4 128.9 135.9 133.3 121.3 120.5 120.4 137.9 126.1 133.2 146.6 103.4 117.2
 
Dataseries Y:
» Textbox « » Textfile « » CSV «
106.8 113.7 102.5 96.6 92.1 95.6 102.3 98.6 98.2 104.5 84 73.8 103.9 106 97.2 102.6 89 93.8 116.7 106.8 98.5 118.7 90 91.9 113.3 113.1 104.1 108.7 96.7 101 116.9 105.8 99 129.4 83 88.9 115.9 104.2 113.4 112.2 100.8 107.3 126.6 102.9 117.9 128.8 87.5 93.8 122.7 126.2 124.6 116.7 115.2 111.1 129.9 113.3 118.5 133.5 102.1 102.4
 
Text written by user:
 
Output produced by software:


Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001


Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-130.0370917683100851
-120.256810752730900
-11-0.177290030543156
-100.196107281670325
-90.161560187160695
-8-0.0480579953269876
-70.197677527917861
-60.10230253890886
-5-0.029541038853089
-40.161073417705934
-30.0633954391746503
-2-0.059352439108144
-10.0940624693915078
0-0.190439300268184
1-0.0690001999464688
20.0380338973503241
3-0.119335033290024
4-0.0247601173266201
50.055690794008488
6-0.0961443337013047
70.111980767520834
80.159424229189611
90.0401995614007164
100.061840667348995
110.157002969917026
120.0598452553469295
130.170971014288187
 
Charts produced by software:
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/25/t1196003613xrhrbra93ptsekw/1ywu51196003949.png (open in new window)
http://127.0.0.1/wessadotnet/public_html/freestatisticsdotorg/blog/date/2007/Nov/25/t1196003613xrhrbra93ptsekw/1ywu51196003949.ps (open in new window)


 
Parameters:
par1 = 1 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 1 ;
 
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
par3 <- as.numeric(par3)
par4 <- as.numeric(par4)
par5 <- as.numeric(par5)
par6 <- as.numeric(par6)
par7 <- as.numeric(par7)
if (par1 == 0) {
x <- log(x)
} else {
x <- (x ^ par1 - 1) / par1
}
if (par5 == 0) {
y <- log(y)
} else {
y <- (y ^ par5 - 1) / par5
}
if (par2 > 0) x <- diff(x,lag=1,difference=par2)
if (par6 > 0) y <- diff(y,lag=1,difference=par6)
if (par3 > 0) x <- diff(x,lag=par4,difference=par3)
if (par7 > 0) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',xlab='Lag (k)'))
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Cross Correlation Function',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'Value',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of X series',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of X series',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of X series',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Seasonal Period (s)',header=TRUE)
a<-table.element(a,par4)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Box-Cox transformation parameter (lambda) of Y series',header=TRUE)
a<-table.element(a,par5)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of non-seasonal differencing (d) of Y series',header=TRUE)
a<-table.element(a,par6)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Degree of seasonal differencing (D) of Y series',header=TRUE)
a<-table.element(a,par7)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'k',header=TRUE)
a<-table.element(a,'rho(Y[t],X[t+k])',header=TRUE)
a<-table.row.end(a)
mylength <- length(r$acf)
myhalf <- floor((mylength-1)/2)
for (i in 1:mylength) {
a<-table.row.start(a)
a<-table.element(a,i-myhalf-1,header=TRUE)
a<-table.element(a,r$acf[i])
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
 





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