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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationThu, 29 Nov 2007 11:04:10 -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/t1196359838p0rmm6e5zfgj4k4.htm/, Retrieved Fri, 29 May 2026 14:57:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7563, Retrieved Fri, 29 May 2026 14:57:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact467

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [opdracht 3 - Q6] [2007-11-29 18:04:10] [20b3c1d23568d98c39f9358fef47a65d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
102,3
108,8
105,9
113,2
95,7
80,9
113,9
98,1
102,8
104,7
95,9
94,6
101,6
103,9
110,3
114,1
96,8
87,4
111,4
97,4
102,9
112,7
97
95,1
96,9
98,6
111,7
109,8
89,9
87,4
104,5
98,1
102,7
105,4
97
97,4
92
101,7
112,6
106,9
92,1
86
104,7
102
103,1
106
96,1
96,2
90,7
102,3
109,4
101
94,7
81
106,2
101,9
96,4
110,4
100,5
98,8
106,9
92,1
86
104,7
102
103,1
106
96,1
96,2
90,7
102,3
109,4
101
94,7
81
106,2
101,9
96,4
110,4
100,5
98,8
Dataseries Y:
Download CSV
Histogram 
139,9
135,6
126,8
134,4
113,5
107,5
133,8
119
125,9
130,1
114,2
111,6
131,2
124,1
127,1
123,4
100,7
100,3
121,6
110,5
110,3
122,7
102,6
101,8
113,6
107,2
116,8
112,5
89
95,2
110,6
102,6
106,4
112,7
103,2
104,2
111,3
115,7
111,6
112,2
92,2
97,1
108,1
107,2
107,2
110,3
97,6
100,6
102,8
105,3
109,5
105,7
93,7
91,7
111,6
109,2
101,2
114,3
100,9
106
109
110,4
110,7
105,7
89,6
83,1
103,5
104,8
93,5
106,7
93,7
84,7
99,2
91,9
94,9
94,1
80,8
72,6
94
80
85,4

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7563&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7563&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7563&T=0

As an alternative you can also use a QR Code:  
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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-15-0.0708196372881533
-140.0097103369605513
-13-0.0308095048550524
-120.0940507470838932
-11-0.0657421799421655
-100.109253028742204
-9-0.0521704052937594
-8-0.0684427769865292
-70.124168638147632
-6-0.094242760320151
-5-0.0619676425733342
-40.19355120917532
-3-0.118596157006409
-2-0.00775752435343795
-10.178008478336223
0-0.362986490116836
10.153602681382357
20.0343587094496553
30.00314686381810303
40.00662088241941571
5-0.0185788043783784
6-0.0678196547691792
70.0129152638784533
80.0727285021039329
9-0.0593178984158765
100.0299751905983832
110.111681250459603
12-0.204605155687251
130.096579929943545
140.0657595788941854
15-0.129249956680675

\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 & 1 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & -0.0708196372881533 \tabularnewline
-14 & 0.0097103369605513 \tabularnewline
-13 & -0.0308095048550524 \tabularnewline
-12 & 0.0940507470838932 \tabularnewline
-11 & -0.0657421799421655 \tabularnewline
-10 & 0.109253028742204 \tabularnewline
-9 & -0.0521704052937594 \tabularnewline
-8 & -0.0684427769865292 \tabularnewline
-7 & 0.124168638147632 \tabularnewline
-6 & -0.094242760320151 \tabularnewline
-5 & -0.0619676425733342 \tabularnewline
-4 & 0.19355120917532 \tabularnewline
-3 & -0.118596157006409 \tabularnewline
-2 & -0.00775752435343795 \tabularnewline
-1 & 0.178008478336223 \tabularnewline
0 & -0.362986490116836 \tabularnewline
1 & 0.153602681382357 \tabularnewline
2 & 0.0343587094496553 \tabularnewline
3 & 0.00314686381810303 \tabularnewline
4 & 0.00662088241941571 \tabularnewline
5 & -0.0185788043783784 \tabularnewline
6 & -0.0678196547691792 \tabularnewline
7 & 0.0129152638784533 \tabularnewline
8 & 0.0727285021039329 \tabularnewline
9 & -0.0593178984158765 \tabularnewline
10 & 0.0299751905983832 \tabularnewline
11 & 0.111681250459603 \tabularnewline
12 & -0.204605155687251 \tabularnewline
13 & 0.096579929943545 \tabularnewline
14 & 0.0657595788941854 \tabularnewline
15 & -0.129249956680675 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7563&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]1[/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]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]-0.0708196372881533[/C][/ROW]
[ROW][C]-14[/C][C]0.0097103369605513[/C][/ROW]
[ROW][C]-13[/C][C]-0.0308095048550524[/C][/ROW]
[ROW][C]-12[/C][C]0.0940507470838932[/C][/ROW]
[ROW][C]-11[/C][C]-0.0657421799421655[/C][/ROW]
[ROW][C]-10[/C][C]0.109253028742204[/C][/ROW]
[ROW][C]-9[/C][C]-0.0521704052937594[/C][/ROW]
[ROW][C]-8[/C][C]-0.0684427769865292[/C][/ROW]
[ROW][C]-7[/C][C]0.124168638147632[/C][/ROW]
[ROW][C]-6[/C][C]-0.094242760320151[/C][/ROW]
[ROW][C]-5[/C][C]-0.0619676425733342[/C][/ROW]
[ROW][C]-4[/C][C]0.19355120917532[/C][/ROW]
[ROW][C]-3[/C][C]-0.118596157006409[/C][/ROW]
[ROW][C]-2[/C][C]-0.00775752435343795[/C][/ROW]
[ROW][C]-1[/C][C]0.178008478336223[/C][/ROW]
[ROW][C]0[/C][C]-0.362986490116836[/C][/ROW]
[ROW][C]1[/C][C]0.153602681382357[/C][/ROW]
[ROW][C]2[/C][C]0.0343587094496553[/C][/ROW]
[ROW][C]3[/C][C]0.00314686381810303[/C][/ROW]
[ROW][C]4[/C][C]0.00662088241941571[/C][/ROW]
[ROW][C]5[/C][C]-0.0185788043783784[/C][/ROW]
[ROW][C]6[/C][C]-0.0678196547691792[/C][/ROW]
[ROW][C]7[/C][C]0.0129152638784533[/C][/ROW]
[ROW][C]8[/C][C]0.0727285021039329[/C][/ROW]
[ROW][C]9[/C][C]-0.0593178984158765[/C][/ROW]
[ROW][C]10[/C][C]0.0299751905983832[/C][/ROW]
[ROW][C]11[/C][C]0.111681250459603[/C][/ROW]
[ROW][C]12[/C][C]-0.204605155687251[/C][/ROW]
[ROW][C]13[/C][C]0.096579929943545[/C][/ROW]
[ROW][C]14[/C][C]0.0657595788941854[/C][/ROW]
[ROW][C]15[/C][C]-0.129249956680675[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7563&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7563&T=1

As an alternative you can also use a QR Code:  
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 series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-15-0.0708196372881533
-140.0097103369605513
-13-0.0308095048550524
-120.0940507470838932
-11-0.0657421799421655
-100.109253028742204
-9-0.0521704052937594
-8-0.0684427769865292
-70.124168638147632
-6-0.094242760320151
-5-0.0619676425733342
-40.19355120917532
-3-0.118596157006409
-2-0.00775752435343795
-10.178008478336223
0-0.362986490116836
10.153602681382357
20.0343587094496553
30.00314686381810303
40.00662088241941571
5-0.0185788043783784
6-0.0678196547691792
70.0129152638784533
80.0727285021039329
9-0.0593178984158765
100.0299751905983832
110.111681250459603
12-0.204605155687251
130.096579929943545
140.0657595788941854
15-0.129249956680675


Figures (Output of Computation)

Input Parameters & R Code

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