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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 computationWed, 28 Nov 2007 12:00:08 -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/28/t1196276041sprqqci3s4at4x1.htm/, Retrieved Thu, 02 May 2024 00:36:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7222, Retrieved Thu, 02 May 2024 00:36:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsexogene variabele = Industriële productie in de verwerkende nijverheid: voedingsmiddelen en dranken endogene variabele = Prijsindexcijfers grondstoffen, algemeen indexcijfer (Inclusief energie)
Estimated Impact170

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] [Cross correlation...] [2007-11-28 19:00:08] [bebbf4ab6ac77d61a56e6916ab0650f9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105,3
101,3
108,4
107,4
109,1
109,5
111,4
110,1
117,0
129,6
113,5
113,3
110,1
107,4
110,1
112,5
106,0
117,6
117,8
113,5
121,2
130,4
115,2
117,9
110,7
107,6
124,3
115,1
112,5
127,9
117,4
119,3
130,4
126,0
125,4
130,5
115,9
108,7
124,0
119,4
118,6
131,3
111,1
124,8
132,3
126,7
131,7
130,9
122,1
113,2
133,6
119,2
129,4
131,4
117,1
130,5
132,3
140,8
137,5
128,6
126,7
120,8
139,3
128,6
131,3
136,3
128,5
Dataseries Y:
Download CSV
Histogram 
75,9
77,7
86,9
90,7
91,0
89,5
92,5
94,1
98,5
96,8
91,2
97,1
104,9
110,9
104,8
94,1
95,8
99,3
101,1
104,0
99,0
105,4
107,1
110,7
117,1
118,7
126,5
127,5
134,6
131,8
135,9
142,7
141,7
153,4
145,0
137,7
148,3
152,2
169,4
168,6
161,1
174,1
179,0
190,6
190,0
181,6
174,8
180,5
196,8
193,8
197,0
216,3
221,4
217,9
229,7
227,4
204,2
196,6
198,8
207,5
190,7
201,6
210,5
223,5
223,8
231,2
244,0

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=7222&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=7222&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7222&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])
-150.268628577029386
-140.293873311857701
-130.34405657279836
-120.34045699181139
-110.389937245317279
-100.44765395769895
-90.511103052883368
-80.549863112719559
-70.565627174930046
-60.557829499163038
-50.558417679605176
-40.615585347236286
-30.607006751228774
-20.62942944367354
-10.674011170048877
00.69597250266343
10.67287527491514
20.64460690067658
30.609249418519529
40.560880361033357
50.530329584916374
60.487350598528781
70.476676577087004
80.441408392815166
90.41045604975847
100.419956695715850
110.388188173572668
120.362347382199145
130.334908482216525
140.300613745821728
150.23697116088138

\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 & 0.268628577029386 \tabularnewline
-14 & 0.293873311857701 \tabularnewline
-13 & 0.34405657279836 \tabularnewline
-12 & 0.34045699181139 \tabularnewline
-11 & 0.389937245317279 \tabularnewline
-10 & 0.44765395769895 \tabularnewline
-9 & 0.511103052883368 \tabularnewline
-8 & 0.549863112719559 \tabularnewline
-7 & 0.565627174930046 \tabularnewline
-6 & 0.557829499163038 \tabularnewline
-5 & 0.558417679605176 \tabularnewline
-4 & 0.615585347236286 \tabularnewline
-3 & 0.607006751228774 \tabularnewline
-2 & 0.62942944367354 \tabularnewline
-1 & 0.674011170048877 \tabularnewline
0 & 0.69597250266343 \tabularnewline
1 & 0.67287527491514 \tabularnewline
2 & 0.64460690067658 \tabularnewline
3 & 0.609249418519529 \tabularnewline
4 & 0.560880361033357 \tabularnewline
5 & 0.530329584916374 \tabularnewline
6 & 0.487350598528781 \tabularnewline
7 & 0.476676577087004 \tabularnewline
8 & 0.441408392815166 \tabularnewline
9 & 0.41045604975847 \tabularnewline
10 & 0.419956695715850 \tabularnewline
11 & 0.388188173572668 \tabularnewline
12 & 0.362347382199145 \tabularnewline
13 & 0.334908482216525 \tabularnewline
14 & 0.300613745821728 \tabularnewline
15 & 0.23697116088138 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7222&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]0.268628577029386[/C][/ROW]
[ROW][C]-14[/C][C]0.293873311857701[/C][/ROW]
[ROW][C]-13[/C][C]0.34405657279836[/C][/ROW]
[ROW][C]-12[/C][C]0.34045699181139[/C][/ROW]
[ROW][C]-11[/C][C]0.389937245317279[/C][/ROW]
[ROW][C]-10[/C][C]0.44765395769895[/C][/ROW]
[ROW][C]-9[/C][C]0.511103052883368[/C][/ROW]
[ROW][C]-8[/C][C]0.549863112719559[/C][/ROW]
[ROW][C]-7[/C][C]0.565627174930046[/C][/ROW]
[ROW][C]-6[/C][C]0.557829499163038[/C][/ROW]
[ROW][C]-5[/C][C]0.558417679605176[/C][/ROW]
[ROW][C]-4[/C][C]0.615585347236286[/C][/ROW]
[ROW][C]-3[/C][C]0.607006751228774[/C][/ROW]
[ROW][C]-2[/C][C]0.62942944367354[/C][/ROW]
[ROW][C]-1[/C][C]0.674011170048877[/C][/ROW]
[ROW][C]0[/C][C]0.69597250266343[/C][/ROW]
[ROW][C]1[/C][C]0.67287527491514[/C][/ROW]
[ROW][C]2[/C][C]0.64460690067658[/C][/ROW]
[ROW][C]3[/C][C]0.609249418519529[/C][/ROW]
[ROW][C]4[/C][C]0.560880361033357[/C][/ROW]
[ROW][C]5[/C][C]0.530329584916374[/C][/ROW]
[ROW][C]6[/C][C]0.487350598528781[/C][/ROW]
[ROW][C]7[/C][C]0.476676577087004[/C][/ROW]
[ROW][C]8[/C][C]0.441408392815166[/C][/ROW]
[ROW][C]9[/C][C]0.41045604975847[/C][/ROW]
[ROW][C]10[/C][C]0.419956695715850[/C][/ROW]
[ROW][C]11[/C][C]0.388188173572668[/C][/ROW]
[ROW][C]12[/C][C]0.362347382199145[/C][/ROW]
[ROW][C]13[/C][C]0.334908482216525[/C][/ROW]
[ROW][C]14[/C][C]0.300613745821728[/C][/ROW]
[ROW][C]15[/C][C]0.23697116088138[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7222&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7222&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])
-150.268628577029386
-140.293873311857701
-130.34405657279836
-120.34045699181139
-110.389937245317279
-100.44765395769895
-90.511103052883368
-80.549863112719559
-70.565627174930046
-60.557829499163038
-50.558417679605176
-40.615585347236286
-30.607006751228774
-20.62942944367354
-10.674011170048877
00.69597250266343
10.67287527491514
20.64460690067658
30.609249418519529
40.560880361033357
50.530329584916374
60.487350598528781
70.476676577087004
80.441408392815166
90.41045604975847
100.419956695715850
110.388188173572668
120.362347382199145
130.334908482216525
140.300613745821728
150.23697116088138


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) 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')