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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSat, 29 Nov 2008 16:41:56 -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/2008/Nov/30/t122800225344tmeuxy017e33h.htm/, Retrieved Tue, 22 Sep 2026 16:38:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26390, Retrieved Tue, 22 Sep 2026 16:38:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact653

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [(Partial) Autocorrelation Function] [Q6 1] [2008-11-29 17:27:48] [aa5573c1db401b164e448aef050955a1]
-   P     [(Partial) Autocorrelation Function] [Q6 2] [2008-11-29 17:36:16] [aa5573c1db401b164e448aef050955a1]
- RMP       [Variance Reduction Matrix] [Q6 VRM] [2008-11-29 17:44:58] [aa5573c1db401b164e448aef050955a1]
- RMPD          [Cross Correlation Function] [Q7 bouwproductie-...] [2008-11-29 23:41:56] [8a1195ff8db4df756ce44b463a631c76] [Current]
Feedback Forum

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
82.7
88.9
105.9
100.8
94
105
58.5
87.6
113.1
112.5
89.6
74.5
82.7
90.1
109.4
96
89.2
109.1
49.1
92.9
107.7
103.5
91.1
79.8
71.9
82.9
90.1
100.7
90.7
108.8
44.1
93.6
107.4
96.5
93.6
76.5
76.7
84
103.3
88.5
99
105.9
44.7
94
107.1
104.8
102.5
77.7
85.2
91.3
106.5
92.4
97.5
107
51.1
98.6
102.2
114.3
99.4
72.5
92.3
99.4
85.9
109.4
97.6
Dataseries Y:
Download CSV
Histogram 
97.4
97
105.4
102.7
98.1
104.5
87.4
89.9
109.8
111.7
98.6
96.9
95.1
97
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
99
100.7
115.5
100.7
109.9
114.6
85.4
100.5
114.8
116.5
112.9
102
106
105.3
118.8
106.1
109.3
117.2
92.5
104.2
112.5
122.4
113.3
100
110.7
112.8
109.8
117.3
109.1

Tables (Output of Computation)





Summary of computational 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 computational 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=26390&T=0

[TABLE]
[ROW][C]Summary of computational 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=26390&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26390&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 computational 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 series0
Seasonal Period (s)1
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])
-15-0.196091047917727
-14-0.220745864614035
-130.0750979251632997
-120.611748422077545
-11-0.144020168367563
-10-0.254353293745687
-9-0.139789730197400
-8-0.189085906131753
-70.232442886426229
-60.305425727317842
-50.144523060078421
-4-0.169420906807685
-3-0.209415654385427
-2-0.280623597071833
-10.145436701240968
00.843179389403469
1-0.197407075222514
2-0.247336188747440
3-0.0888395053529347
4-0.194642952275513
50.301003561132426
60.314393565706403
70.095634662822107
8-0.0974124919989134
9-0.182154270771597
10-0.230256734695631
110.203569061424562
120.615883428798488
13-0.144941362675250
14-0.126223549424623
15-0.0951598695609897

\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) & 1 \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
-15 & -0.196091047917727 \tabularnewline
-14 & -0.220745864614035 \tabularnewline
-13 & 0.0750979251632997 \tabularnewline
-12 & 0.611748422077545 \tabularnewline
-11 & -0.144020168367563 \tabularnewline
-10 & -0.254353293745687 \tabularnewline
-9 & -0.139789730197400 \tabularnewline
-8 & -0.189085906131753 \tabularnewline
-7 & 0.232442886426229 \tabularnewline
-6 & 0.305425727317842 \tabularnewline
-5 & 0.144523060078421 \tabularnewline
-4 & -0.169420906807685 \tabularnewline
-3 & -0.209415654385427 \tabularnewline
-2 & -0.280623597071833 \tabularnewline
-1 & 0.145436701240968 \tabularnewline
0 & 0.843179389403469 \tabularnewline
1 & -0.197407075222514 \tabularnewline
2 & -0.247336188747440 \tabularnewline
3 & -0.0888395053529347 \tabularnewline
4 & -0.194642952275513 \tabularnewline
5 & 0.301003561132426 \tabularnewline
6 & 0.314393565706403 \tabularnewline
7 & 0.095634662822107 \tabularnewline
8 & -0.0974124919989134 \tabularnewline
9 & -0.182154270771597 \tabularnewline
10 & -0.230256734695631 \tabularnewline
11 & 0.203569061424562 \tabularnewline
12 & 0.615883428798488 \tabularnewline
13 & -0.144941362675250 \tabularnewline
14 & -0.126223549424623 \tabularnewline
15 & -0.0951598695609897 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26390&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]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]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]-15[/C][C]-0.196091047917727[/C][/ROW]
[ROW][C]-14[/C][C]-0.220745864614035[/C][/ROW]
[ROW][C]-13[/C][C]0.0750979251632997[/C][/ROW]
[ROW][C]-12[/C][C]0.611748422077545[/C][/ROW]
[ROW][C]-11[/C][C]-0.144020168367563[/C][/ROW]
[ROW][C]-10[/C][C]-0.254353293745687[/C][/ROW]
[ROW][C]-9[/C][C]-0.139789730197400[/C][/ROW]
[ROW][C]-8[/C][C]-0.189085906131753[/C][/ROW]
[ROW][C]-7[/C][C]0.232442886426229[/C][/ROW]
[ROW][C]-6[/C][C]0.305425727317842[/C][/ROW]
[ROW][C]-5[/C][C]0.144523060078421[/C][/ROW]
[ROW][C]-4[/C][C]-0.169420906807685[/C][/ROW]
[ROW][C]-3[/C][C]-0.209415654385427[/C][/ROW]
[ROW][C]-2[/C][C]-0.280623597071833[/C][/ROW]
[ROW][C]-1[/C][C]0.145436701240968[/C][/ROW]
[ROW][C]0[/C][C]0.843179389403469[/C][/ROW]
[ROW][C]1[/C][C]-0.197407075222514[/C][/ROW]
[ROW][C]2[/C][C]-0.247336188747440[/C][/ROW]
[ROW][C]3[/C][C]-0.0888395053529347[/C][/ROW]
[ROW][C]4[/C][C]-0.194642952275513[/C][/ROW]
[ROW][C]5[/C][C]0.301003561132426[/C][/ROW]
[ROW][C]6[/C][C]0.314393565706403[/C][/ROW]
[ROW][C]7[/C][C]0.095634662822107[/C][/ROW]
[ROW][C]8[/C][C]-0.0974124919989134[/C][/ROW]
[ROW][C]9[/C][C]-0.182154270771597[/C][/ROW]
[ROW][C]10[/C][C]-0.230256734695631[/C][/ROW]
[ROW][C]11[/C][C]0.203569061424562[/C][/ROW]
[ROW][C]12[/C][C]0.615883428798488[/C][/ROW]
[ROW][C]13[/C][C]-0.144941362675250[/C][/ROW]
[ROW][C]14[/C][C]-0.126223549424623[/C][/ROW]
[ROW][C]15[/C][C]-0.0951598695609897[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26390&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26390&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 series0
Seasonal Period (s)1
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])
-15-0.196091047917727
-14-0.220745864614035
-130.0750979251632997
-120.611748422077545
-11-0.144020168367563
-10-0.254353293745687
-9-0.139789730197400
-8-0.189085906131753
-70.232442886426229
-60.305425727317842
-50.144523060078421
-4-0.169420906807685
-3-0.209415654385427
-2-0.280623597071833
-10.145436701240968
00.843179389403469
1-0.197407075222514
2-0.247336188747440
3-0.0888395053529347
4-0.194642952275513
50.301003561132426
60.314393565706403
70.095634662822107
8-0.0974124919989134
9-0.182154270771597
10-0.230256734695631
110.203569061424562
120.615883428798488
13-0.144941362675250
14-0.126223549424623
15-0.0951598695609897


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ; 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) y <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',ylab='CCF',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')