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Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 25 Nov 2007 13:00:03 -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/25/t1196020296tnioyowai0wy6ls.htm/, Retrieved Sat, 04 May 2024 07:48:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6542, Retrieved Sat, 04 May 2024 07:48:53 +0000
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Original text written by user:Q6
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact187
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [inducing stationa...] [2007-11-25 20:00:03] [a04acf73ce4b7e85f8287f21ada159c8] [Current]
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Dataseries X:
0,9383
0,9217
0,9095
0,892
0,8742
0,8532
0,8607
0,9005
0,9111
0,9059
0,8883
0,8924
0,8833
0,87
0,8758
0,8858
0,917
0,9554
0,9922
0,9778
0,9808
0,9811
1,0014
1,0183
1,0622
1,0773
1,0807
1,0848
1,1582
1,1663
1,1372
1,1139
1,1222
1,1692
1,1702
1,2286
1,2613
1,2646
1,2262
1,1985
1,2007
1,2138
1,2266
1,2176
1,2218
1,249
1,2991
1,3408
1,3119
1,3014
1,3201
1,2938
1,2694
1,2165
1,2037
1,2292
1,2256
1,2015
1,1786
1,1856
1,2103
1,1938
1,202
1,2271
1,277
1,265
1,2684
1,2811
1,2727
1,2611
1,2881
1,3213
1,2999
1,3074
1,3242
1,3516
1,3511
1,3419
1,3716
1,3622
1,3896
Dataseries Y:
90,8
96,4
90
92,1
97,2
95,1
88,5
91
90,5
75
66,3
66
68,4
70,6
83,9
90,1
90,6
87,1
90,8
94,1
99,8
96,8
87
96,3
107,1
115,2
106,1
89,5
91,3
97,6
100,7
104,6
94,7
101,8
102,5
105,3
110,3
109,8
117,3
118,8
131,3
125,9
133,1
147
145,8
164,4
149,8
137,7
151,7
156,8
180
180,4
170,4
191,6
199,5
218,2
217,5
205
194
199,3
219,3
211,1
215,2
240,2
242,2
240,7
255,4
253
218,2
203,7
205,6
215,6
188,5
202,9
214
230,3
230
241
259,6
247,8
270,3




Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 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=6542&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]3 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=6542&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6542&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 time3 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 series1
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-160.160686854883218
-150.107570315058082
-140.096942757350884
-130.0158615646499524
-12-0.124002301372526
-11-0.0873825209499656
-10-0.0327141410806547
-9-0.0115432451127374
-80.0820406865784614
-70.22089130841312
-6-0.0589066474003619
-5-0.0682193297037775
-4-0.0087225412739767
-30.131234107005216
-2-0.169450623425674
-1-0.131584426458338
00.184373172237847
1-0.02385416333977
2-0.0615549539322165
3-0.116883481939126
40.195320437397008
50.0457356235125076
6-0.227043419833176
70.0171592330038592
8-0.128418376176179
9-0.068175181882659
100.0457782797942341
110.102927302335834
120.0176416952859081
13-0.128183697738866
14-0.0579493430285037
15-0.0477550188058538
16-0.0152639641059269

\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 & 1 \tabularnewline
Degree of seasonal differencing (D) of X series & 0 \tabularnewline
Seasonal Period (s) & 1 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 1 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & 0.160686854883218 \tabularnewline
-15 & 0.107570315058082 \tabularnewline
-14 & 0.096942757350884 \tabularnewline
-13 & 0.0158615646499524 \tabularnewline
-12 & -0.124002301372526 \tabularnewline
-11 & -0.0873825209499656 \tabularnewline
-10 & -0.0327141410806547 \tabularnewline
-9 & -0.0115432451127374 \tabularnewline
-8 & 0.0820406865784614 \tabularnewline
-7 & 0.22089130841312 \tabularnewline
-6 & -0.0589066474003619 \tabularnewline
-5 & -0.0682193297037775 \tabularnewline
-4 & -0.0087225412739767 \tabularnewline
-3 & 0.131234107005216 \tabularnewline
-2 & -0.169450623425674 \tabularnewline
-1 & -0.131584426458338 \tabularnewline
0 & 0.184373172237847 \tabularnewline
1 & -0.02385416333977 \tabularnewline
2 & -0.0615549539322165 \tabularnewline
3 & -0.116883481939126 \tabularnewline
4 & 0.195320437397008 \tabularnewline
5 & 0.0457356235125076 \tabularnewline
6 & -0.227043419833176 \tabularnewline
7 & 0.0171592330038592 \tabularnewline
8 & -0.128418376176179 \tabularnewline
9 & -0.068175181882659 \tabularnewline
10 & 0.0457782797942341 \tabularnewline
11 & 0.102927302335834 \tabularnewline
12 & 0.0176416952859081 \tabularnewline
13 & -0.128183697738866 \tabularnewline
14 & -0.0579493430285037 \tabularnewline
15 & -0.0477550188058538 \tabularnewline
16 & -0.0152639641059269 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6542&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]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]0[/C][/ROW]
[ROW][C]Seasonal Period (s)[/C][C]1[/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]1[/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]-16[/C][C]0.160686854883218[/C][/ROW]
[ROW][C]-15[/C][C]0.107570315058082[/C][/ROW]
[ROW][C]-14[/C][C]0.096942757350884[/C][/ROW]
[ROW][C]-13[/C][C]0.0158615646499524[/C][/ROW]
[ROW][C]-12[/C][C]-0.124002301372526[/C][/ROW]
[ROW][C]-11[/C][C]-0.0873825209499656[/C][/ROW]
[ROW][C]-10[/C][C]-0.0327141410806547[/C][/ROW]
[ROW][C]-9[/C][C]-0.0115432451127374[/C][/ROW]
[ROW][C]-8[/C][C]0.0820406865784614[/C][/ROW]
[ROW][C]-7[/C][C]0.22089130841312[/C][/ROW]
[ROW][C]-6[/C][C]-0.0589066474003619[/C][/ROW]
[ROW][C]-5[/C][C]-0.0682193297037775[/C][/ROW]
[ROW][C]-4[/C][C]-0.0087225412739767[/C][/ROW]
[ROW][C]-3[/C][C]0.131234107005216[/C][/ROW]
[ROW][C]-2[/C][C]-0.169450623425674[/C][/ROW]
[ROW][C]-1[/C][C]-0.131584426458338[/C][/ROW]
[ROW][C]0[/C][C]0.184373172237847[/C][/ROW]
[ROW][C]1[/C][C]-0.02385416333977[/C][/ROW]
[ROW][C]2[/C][C]-0.0615549539322165[/C][/ROW]
[ROW][C]3[/C][C]-0.116883481939126[/C][/ROW]
[ROW][C]4[/C][C]0.195320437397008[/C][/ROW]
[ROW][C]5[/C][C]0.0457356235125076[/C][/ROW]
[ROW][C]6[/C][C]-0.227043419833176[/C][/ROW]
[ROW][C]7[/C][C]0.0171592330038592[/C][/ROW]
[ROW][C]8[/C][C]-0.128418376176179[/C][/ROW]
[ROW][C]9[/C][C]-0.068175181882659[/C][/ROW]
[ROW][C]10[/C][C]0.0457782797942341[/C][/ROW]
[ROW][C]11[/C][C]0.102927302335834[/C][/ROW]
[ROW][C]12[/C][C]0.0176416952859081[/C][/ROW]
[ROW][C]13[/C][C]-0.128183697738866[/C][/ROW]
[ROW][C]14[/C][C]-0.0579493430285037[/C][/ROW]
[ROW][C]15[/C][C]-0.0477550188058538[/C][/ROW]
[ROW][C]16[/C][C]-0.0152639641059269[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6542&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6542&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 series1
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-160.160686854883218
-150.107570315058082
-140.096942757350884
-130.0158615646499524
-12-0.124002301372526
-11-0.0873825209499656
-10-0.0327141410806547
-9-0.0115432451127374
-80.0820406865784614
-70.22089130841312
-6-0.0589066474003619
-5-0.0682193297037775
-4-0.0087225412739767
-30.131234107005216
-2-0.169450623425674
-1-0.131584426458338
00.184373172237847
1-0.02385416333977
2-0.0615549539322165
3-0.116883481939126
40.195320437397008
50.0457356235125076
6-0.227043419833176
70.0171592330038592
8-0.128418376176179
9-0.068175181882659
100.0457782797942341
110.102927302335834
120.0176416952859081
13-0.128183697738866
14-0.0579493430285037
15-0.0477550188058538
16-0.0152639641059269



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