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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 computationFri, 23 Nov 2007 03:24:21 -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/23/t1195813008i87pg817a7oy1rp.htm/, Retrieved Sun, 28 Apr 2024 21:25:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6131, Retrieved Sun, 28 Apr 2024 21:25:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsGroep 1, WS7, Q6
Estimated Impact236

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] [WS7, Q6] [2007-11-23 10:24:21] [ce556af355e2eff84137e549c6ea8397] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97,3
101
113,2
101
105,7
113,9
86,4
96,5
103,3
114,9
105,8
94,2
98,4
99,4
108,8
112,6
104,4
112,2
81,1
97,1
112,6
113,8
107,8
103,2
103,3
101,2
107,7
110,4
101,9
115,9
89,9
88,6
117,2
123,9
100
103,6
94,1
98,7
119,5
112,7
104,4
124,7
89,1
97
121,6
118,8
114
111,5
97,2
102,5
113,4
109,8
104,9
126,1
80
96,8
117,2
112,3
117,3
111,1
102,2
104,3
122,9
107,6
121,3
131,5
89
104,4
128,9
135,9
133,3
121,3
120,5
120,4
137,9
126,1
133,2
146,6
103,4
117,2
Dataseries Y:
Download CSV
Histogram 
106,7
110,2
125,9
100,1
106,4
114,8
81,3
87
104,2
108
105
94,5
92
95,9
108,8
103,4
102,1
110,1
83,2
82,7
106,8
113,7
102,5
96,6
92,1
95,6
102,3
98,6
98,2
104,5
84
73,8
103,9
106
97,2
102,6
89
93,8
116,7
106,8
98,5
118,7
90
91,9
113,3
113,1
104,1
108,7
96,7
101
116,9
105,8
99
129,4
83
88,9
115,9
104,2
113,4
112,2
100,8
107,3
126,6
102,9
117,9
128,8
87,5
93,8
122,7
126,2
124,6
116,7
115,2
111,1
129,9
113,3
118,5
133,5
102,1
102,4

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=6131&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=6131&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6131&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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t-k])
-150.204944288735889
-140.0172139533481503
-130.116228910760239
-120.318902283630745
-110.0593039831280309
-100.186940020783432
-90.162705413197874
-80.0252635806934181
-70.184198267432947
-60.213273329137242
-50.112660351380543
-40.163722127505784
-30.0360561479718879
-2-0.0465682985111230
-10.0282949528958431
0-0.180456593438629
10.0196266951120851
20.0451193284237828
3-0.0260144537898954
40.0254167634357681
50.0116320539959645
6-0.0147533570446718
70.0780399569990739
80.0832100403823283
90.0677786495583741
100.0173985488298957
110.0359695058340154
12-0.0407714029820687
130.0314938516956346
140.0358487673846205
15-0.0474817808194581

\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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t-k]) \tabularnewline
-15 & 0.204944288735889 \tabularnewline
-14 & 0.0172139533481503 \tabularnewline
-13 & 0.116228910760239 \tabularnewline
-12 & 0.318902283630745 \tabularnewline
-11 & 0.0593039831280309 \tabularnewline
-10 & 0.186940020783432 \tabularnewline
-9 & 0.162705413197874 \tabularnewline
-8 & 0.0252635806934181 \tabularnewline
-7 & 0.184198267432947 \tabularnewline
-6 & 0.213273329137242 \tabularnewline
-5 & 0.112660351380543 \tabularnewline
-4 & 0.163722127505784 \tabularnewline
-3 & 0.0360561479718879 \tabularnewline
-2 & -0.0465682985111230 \tabularnewline
-1 & 0.0282949528958431 \tabularnewline
0 & -0.180456593438629 \tabularnewline
1 & 0.0196266951120851 \tabularnewline
2 & 0.0451193284237828 \tabularnewline
3 & -0.0260144537898954 \tabularnewline
4 & 0.0254167634357681 \tabularnewline
5 & 0.0116320539959645 \tabularnewline
6 & -0.0147533570446718 \tabularnewline
7 & 0.0780399569990739 \tabularnewline
8 & 0.0832100403823283 \tabularnewline
9 & 0.0677786495583741 \tabularnewline
10 & 0.0173985488298957 \tabularnewline
11 & 0.0359695058340154 \tabularnewline
12 & -0.0407714029820687 \tabularnewline
13 & 0.0314938516956346 \tabularnewline
14 & 0.0358487673846205 \tabularnewline
15 & -0.0474817808194581 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6131&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]0[/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]0.204944288735889[/C][/ROW]
[ROW][C]-14[/C][C]0.0172139533481503[/C][/ROW]
[ROW][C]-13[/C][C]0.116228910760239[/C][/ROW]
[ROW][C]-12[/C][C]0.318902283630745[/C][/ROW]
[ROW][C]-11[/C][C]0.0593039831280309[/C][/ROW]
[ROW][C]-10[/C][C]0.186940020783432[/C][/ROW]
[ROW][C]-9[/C][C]0.162705413197874[/C][/ROW]
[ROW][C]-8[/C][C]0.0252635806934181[/C][/ROW]
[ROW][C]-7[/C][C]0.184198267432947[/C][/ROW]
[ROW][C]-6[/C][C]0.213273329137242[/C][/ROW]
[ROW][C]-5[/C][C]0.112660351380543[/C][/ROW]
[ROW][C]-4[/C][C]0.163722127505784[/C][/ROW]
[ROW][C]-3[/C][C]0.0360561479718879[/C][/ROW]
[ROW][C]-2[/C][C]-0.0465682985111230[/C][/ROW]
[ROW][C]-1[/C][C]0.0282949528958431[/C][/ROW]
[ROW][C]0[/C][C]-0.180456593438629[/C][/ROW]
[ROW][C]1[/C][C]0.0196266951120851[/C][/ROW]
[ROW][C]2[/C][C]0.0451193284237828[/C][/ROW]
[ROW][C]3[/C][C]-0.0260144537898954[/C][/ROW]
[ROW][C]4[/C][C]0.0254167634357681[/C][/ROW]
[ROW][C]5[/C][C]0.0116320539959645[/C][/ROW]
[ROW][C]6[/C][C]-0.0147533570446718[/C][/ROW]
[ROW][C]7[/C][C]0.0780399569990739[/C][/ROW]
[ROW][C]8[/C][C]0.0832100403823283[/C][/ROW]
[ROW][C]9[/C][C]0.0677786495583741[/C][/ROW]
[ROW][C]10[/C][C]0.0173985488298957[/C][/ROW]
[ROW][C]11[/C][C]0.0359695058340154[/C][/ROW]
[ROW][C]12[/C][C]-0.0407714029820687[/C][/ROW]
[ROW][C]13[/C][C]0.0314938516956346[/C][/ROW]
[ROW][C]14[/C][C]0.0358487673846205[/C][/ROW]
[ROW][C]15[/C][C]-0.0474817808194581[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6131&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6131&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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t-k])
-150.204944288735889
-140.0172139533481503
-130.116228910760239
-120.318902283630745
-110.0593039831280309
-100.186940020783432
-90.162705413197874
-80.0252635806934181
-70.184198267432947
-60.213273329137242
-50.112660351380543
-40.163722127505784
-30.0360561479718879
-2-0.0465682985111230
-10.0282949528958431
0-0.180456593438629
10.0196266951120851
20.0451193284237828
3-0.0260144537898954
40.0254167634357681
50.0116320539959645
6-0.0147533570446718
70.0780399569990739
80.0832100403823283
90.0677786495583741
100.0173985488298957
110.0359695058340154
12-0.0407714029820687
130.0314938516956346
140.0358487673846205
15-0.0474817808194581


Figures (Output of Computation)

Input Parameters & R Code

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