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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationThu, 29 Nov 2007 07:29:43 -0700
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2007/Nov/29/t1196345995w30uvzhsr8arz1b.htm/, Retrieved Fri, 03 May 2024 08:16:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7490, Retrieved Fri, 03 May 2024 08:16:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact153
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [Stationarity in t...] [2007-11-29 14:29:43] [fea8286ffce1c0d00dd375fb36de4323] [Current]
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Dataseries X:
98.8
100.5
110.4
96.4
101.9
106.2
81.0
94.7
101.0
109.4
102.3
90.7
96.2
96.1
106.0
103.1
102.0
104.7
86.0
92.1
106.9
112.6
101.7
92.0
97.4
97.0
105.4
102.7
98.1
104.5
87.4
89.9
109.8
111.7
98.6
96.9
95.1
97.0
112.7
102.9
97.4
111.4
87.4
96.8
114.1
110.3
103.9
101.6
94.6
95.9
104.7
102.8
98.1
113.9
80.9
95.7
113.2
105.9
108.8
102.3
Dataseries Y:
50.7
46.8
61.7
65.5
58.4
52.3
61.1
49.1
58.5
50.6
53.5
58.4
55.9
41.5
53.0
64.6
57.4
49.8
55.3
48.5
49.5
47.7
52.6
53.3
56.4
50.7
51.2
60.4
56.1
54.0
58.7
48.1
50.5
51.4
57.8
61.7
60.8
47.9
53.3
68.0
57.2
69.4
69.6
56.1
55.5
54.7
53.8
63.0
58.0
41.1
48.8
57.2
50.3
54.3
51.9
51.0
43.9
54.9
52.9
51.4




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7490&T=0

[TABLE]
[ROW][C]Summary of compuational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7490&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7490&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 series0
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 series0
krho(Y[t],X[t+k])
-140.184380457918534
-130.212528225244194
-12-0.179866532339249
-11-0.368909662403477
-100.0330106321091411
-90.00115879618289457
-8-0.0325337402785099
-70.298251825249407
-60.0929983919405215
-5-0.375346144027658
-4-0.118993971917313
-30.099254615733515
-20.194304700687420
-10.362831483081113
0-0.113810708631561
1-0.340632165938302
20.085194995140856
3-0.0462424461455985
4-0.089352239607855
50.429550984893491
60.196644708182714
7-0.363021385533852
8-0.204878982211949
90.0437191568637941
100.105038335586105
110.305089672629058
12-0.0804452884158739
13-0.264860038861465
140.0943523667229226

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 0 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & 0.184380457918534 \tabularnewline
-13 & 0.212528225244194 \tabularnewline
-12 & -0.179866532339249 \tabularnewline
-11 & -0.368909662403477 \tabularnewline
-10 & 0.0330106321091411 \tabularnewline
-9 & 0.00115879618289457 \tabularnewline
-8 & -0.0325337402785099 \tabularnewline
-7 & 0.298251825249407 \tabularnewline
-6 & 0.0929983919405215 \tabularnewline
-5 & -0.375346144027658 \tabularnewline
-4 & -0.118993971917313 \tabularnewline
-3 & 0.099254615733515 \tabularnewline
-2 & 0.194304700687420 \tabularnewline
-1 & 0.362831483081113 \tabularnewline
0 & -0.113810708631561 \tabularnewline
1 & -0.340632165938302 \tabularnewline
2 & 0.085194995140856 \tabularnewline
3 & -0.0462424461455985 \tabularnewline
4 & -0.089352239607855 \tabularnewline
5 & 0.429550984893491 \tabularnewline
6 & 0.196644708182714 \tabularnewline
7 & -0.363021385533852 \tabularnewline
8 & -0.204878982211949 \tabularnewline
9 & 0.0437191568637941 \tabularnewline
10 & 0.105038335586105 \tabularnewline
11 & 0.305089672629058 \tabularnewline
12 & -0.0804452884158739 \tabularnewline
13 & -0.264860038861465 \tabularnewline
14 & 0.0943523667229226 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7490&T=1

[TABLE]
[ROW][C]Cross Correlation Function[/C][/ROW]
[ROW][C]Parameter[/C][C]Value[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of X series[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]0[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]12[/C][/ROW]
[ROW][C]Box-Cox transformation parameter (lambda) of Y series[/C][C]1[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]0[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]0.184380457918534[/C][/ROW]
[ROW][C]-13[/C][C]0.212528225244194[/C][/ROW]
[ROW][C]-12[/C][C]-0.179866532339249[/C][/ROW]
[ROW][C]-11[/C][C]-0.368909662403477[/C][/ROW]
[ROW][C]-10[/C][C]0.0330106321091411[/C][/ROW]
[ROW][C]-9[/C][C]0.00115879618289457[/C][/ROW]
[ROW][C]-8[/C][C]-0.0325337402785099[/C][/ROW]
[ROW][C]-7[/C][C]0.298251825249407[/C][/ROW]
[ROW][C]-6[/C][C]0.0929983919405215[/C][/ROW]
[ROW][C]-5[/C][C]-0.375346144027658[/C][/ROW]
[ROW][C]-4[/C][C]-0.118993971917313[/C][/ROW]
[ROW][C]-3[/C][C]0.099254615733515[/C][/ROW]
[ROW][C]-2[/C][C]0.194304700687420[/C][/ROW]
[ROW][C]-1[/C][C]0.362831483081113[/C][/ROW]
[ROW][C]0[/C][C]-0.113810708631561[/C][/ROW]
[ROW][C]1[/C][C]-0.340632165938302[/C][/ROW]
[ROW][C]2[/C][C]0.085194995140856[/C][/ROW]
[ROW][C]3[/C][C]-0.0462424461455985[/C][/ROW]
[ROW][C]4[/C][C]-0.089352239607855[/C][/ROW]
[ROW][C]5[/C][C]0.429550984893491[/C][/ROW]
[ROW][C]6[/C][C]0.196644708182714[/C][/ROW]
[ROW][C]7[/C][C]-0.363021385533852[/C][/ROW]
[ROW][C]8[/C][C]-0.204878982211949[/C][/ROW]
[ROW][C]9[/C][C]0.0437191568637941[/C][/ROW]
[ROW][C]10[/C][C]0.105038335586105[/C][/ROW]
[ROW][C]11[/C][C]0.305089672629058[/C][/ROW]
[ROW][C]12[/C][C]-0.0804452884158739[/C][/ROW]
[ROW][C]13[/C][C]-0.264860038861465[/C][/ROW]
[ROW][C]14[/C][C]0.0943523667229226[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7490&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7490&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

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 series0
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 series0
krho(Y[t],X[t+k])
-140.184380457918534
-130.212528225244194
-12-0.179866532339249
-11-0.368909662403477
-100.0330106321091411
-90.00115879618289457
-8-0.0325337402785099
-70.298251825249407
-60.0929983919405215
-5-0.375346144027658
-4-0.118993971917313
-30.099254615733515
-20.194304700687420
-10.362831483081113
0-0.113810708631561
1-0.340632165938302
20.085194995140856
3-0.0462424461455985
4-0.089352239607855
50.429550984893491
60.196644708182714
7-0.363021385533852
8-0.204878982211949
90.0437191568637941
100.105038335586105
110.305089672629058
12-0.0804452884158739
13-0.264860038861465
140.0943523667229226



Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
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')