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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, 22 Nov 2007 02:28:22 -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/22/t1195723257vr4tbpcz6t2jj1u.htm/, Retrieved Thu, 02 May 2024 14:00:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=5920, Retrieved Thu, 02 May 2024 14:00:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInducing Stationarity, Q5, Cross Correlation
Estimated Impact203

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] [Inducing Stationa...] [2007-11-22 09:28:22] [31c081e22155d2286c083ea41082003f] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101,5
126,6
93,9
89,8
93,4
101,5
110,4
105,9
108,4
113,9
86,1
69,4
101,2
100,5
98
106,6
90,1
96,9
125,9
112
100
123,9
79,8
83,4
113,6
112,9
104
109,9
99
106,3
128,9
111,1
102,9
130
87
87,5
117,6
103,4
110,8
112,6
102,5
112,4
135,6
105,1
127,7
137
91
90,5
122,4
123,3
124,3
120
118,1
119
142,7
123,6
129,6
146,9
108,7
99,4
Dataseries Y:
Download CSV
Histogram 
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5
115,7
113,6
129,7
112
116,8
126,3
112,9
115,9

Tables (Output of Computation)





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=5920&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=5920&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5920&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 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 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])
-14-0.154551749335059
-13-0.162033062153822
-120.392888869954226
-11-0.0335546592720612
-10-0.258796149779621
-90.238456354495266
-8-0.0077137104398625
-70.0141436883390533
-60.495932857774105
-50.134157381804131
-4-0.0678174140700726
-30.258740823186658
-2-0.208886070342851
-1-0.0831380831491027
00.704708274931032
10.0923446333059778
20.0202025631748818
30.474930722786954
40.0565212654825738
50.147917956470911
60.595921589492243
70.137338354446251
80.102532953501372
90.270281875043985
10-0.271111443911877
11-0.0799682960495309
120.464955587953067
13-0.0141831147245367
14-0.00353054147341108

\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
-14 & -0.154551749335059 \tabularnewline
-13 & -0.162033062153822 \tabularnewline
-12 & 0.392888869954226 \tabularnewline
-11 & -0.0335546592720612 \tabularnewline
-10 & -0.258796149779621 \tabularnewline
-9 & 0.238456354495266 \tabularnewline
-8 & -0.0077137104398625 \tabularnewline
-7 & 0.0141436883390533 \tabularnewline
-6 & 0.495932857774105 \tabularnewline
-5 & 0.134157381804131 \tabularnewline
-4 & -0.0678174140700726 \tabularnewline
-3 & 0.258740823186658 \tabularnewline
-2 & -0.208886070342851 \tabularnewline
-1 & -0.0831380831491027 \tabularnewline
0 & 0.704708274931032 \tabularnewline
1 & 0.0923446333059778 \tabularnewline
2 & 0.0202025631748818 \tabularnewline
3 & 0.474930722786954 \tabularnewline
4 & 0.0565212654825738 \tabularnewline
5 & 0.147917956470911 \tabularnewline
6 & 0.595921589492243 \tabularnewline
7 & 0.137338354446251 \tabularnewline
8 & 0.102532953501372 \tabularnewline
9 & 0.270281875043985 \tabularnewline
10 & -0.271111443911877 \tabularnewline
11 & -0.0799682960495309 \tabularnewline
12 & 0.464955587953067 \tabularnewline
13 & -0.0141831147245367 \tabularnewline
14 & -0.00353054147341108 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=5920&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]-14[/C][C]-0.154551749335059[/C][/ROW]
[ROW][C]-13[/C][C]-0.162033062153822[/C][/ROW]
[ROW][C]-12[/C][C]0.392888869954226[/C][/ROW]
[ROW][C]-11[/C][C]-0.0335546592720612[/C][/ROW]
[ROW][C]-10[/C][C]-0.258796149779621[/C][/ROW]
[ROW][C]-9[/C][C]0.238456354495266[/C][/ROW]
[ROW][C]-8[/C][C]-0.0077137104398625[/C][/ROW]
[ROW][C]-7[/C][C]0.0141436883390533[/C][/ROW]
[ROW][C]-6[/C][C]0.495932857774105[/C][/ROW]
[ROW][C]-5[/C][C]0.134157381804131[/C][/ROW]
[ROW][C]-4[/C][C]-0.0678174140700726[/C][/ROW]
[ROW][C]-3[/C][C]0.258740823186658[/C][/ROW]
[ROW][C]-2[/C][C]-0.208886070342851[/C][/ROW]
[ROW][C]-1[/C][C]-0.0831380831491027[/C][/ROW]
[ROW][C]0[/C][C]0.704708274931032[/C][/ROW]
[ROW][C]1[/C][C]0.0923446333059778[/C][/ROW]
[ROW][C]2[/C][C]0.0202025631748818[/C][/ROW]
[ROW][C]3[/C][C]0.474930722786954[/C][/ROW]
[ROW][C]4[/C][C]0.0565212654825738[/C][/ROW]
[ROW][C]5[/C][C]0.147917956470911[/C][/ROW]
[ROW][C]6[/C][C]0.595921589492243[/C][/ROW]
[ROW][C]7[/C][C]0.137338354446251[/C][/ROW]
[ROW][C]8[/C][C]0.102532953501372[/C][/ROW]
[ROW][C]9[/C][C]0.270281875043985[/C][/ROW]
[ROW][C]10[/C][C]-0.271111443911877[/C][/ROW]
[ROW][C]11[/C][C]-0.0799682960495309[/C][/ROW]
[ROW][C]12[/C][C]0.464955587953067[/C][/ROW]
[ROW][C]13[/C][C]-0.0141831147245367[/C][/ROW]
[ROW][C]14[/C][C]-0.00353054147341108[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=5920&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=5920&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])
-14-0.154551749335059
-13-0.162033062153822
-120.392888869954226
-11-0.0335546592720612
-10-0.258796149779621
-90.238456354495266
-8-0.0077137104398625
-70.0141436883390533
-60.495932857774105
-50.134157381804131
-4-0.0678174140700726
-30.258740823186658
-2-0.208886070342851
-1-0.0831380831491027
00.704708274931032
10.0923446333059778
20.0202025631748818
30.474930722786954
40.0565212654825738
50.147917956470911
60.595921589492243
70.137338354446251
80.102532953501372
90.270281875043985
10-0.271111443911877
11-0.0799682960495309
120.464955587953067
13-0.0141831147245367
14-0.00353054147341108


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 12 ;
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) 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')