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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 computationMon, 26 Nov 2007 13:16:01 -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/26/t1196107670hznymll95sa8mgj.htm/, Retrieved Thu, 02 May 2024 22:16:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6674, Retrieved Thu, 02 May 2024 22:16:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsCross Correlation van totaal en Producten van metaal
Estimated Impact188

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] [Q6] [2007-11-26 20:16:01] [ae3f0dfb5dab6ea17524363c550229d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
Dataseries Y:
Download CSV
Histogram 
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

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=6674&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=6674&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6674&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])
-150.0375218762182277
-14-0.158191878325947
-13-0.00605342073586711
-120.239326673840961
-11-0.0407831957348798
-100.0791792247422096
-90.0584385573803656
-8-0.0824082444561495
-70.14205701808935
-60.149321832360581
-50.0522205984462898
-40.186369739354244
-30.073346044851378
-20.0127645143729394
-10.171746824136192
00.0423903400293619
10.142445353361771
20.187181504683528
30.0521864680892183
40.0423000430012191
50.108513018152896
60.083708822754703
70.0945016168404909
80.132915511748760
90.074696134033715
10-0.00629687246836543
110.119805664650469
120.0984344220100687
130.127647625620536
140.156844223432599
150.0415697961663499

\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 & 0.0375218762182277 \tabularnewline
-14 & -0.158191878325947 \tabularnewline
-13 & -0.00605342073586711 \tabularnewline
-12 & 0.239326673840961 \tabularnewline
-11 & -0.0407831957348798 \tabularnewline
-10 & 0.0791792247422096 \tabularnewline
-9 & 0.0584385573803656 \tabularnewline
-8 & -0.0824082444561495 \tabularnewline
-7 & 0.14205701808935 \tabularnewline
-6 & 0.149321832360581 \tabularnewline
-5 & 0.0522205984462898 \tabularnewline
-4 & 0.186369739354244 \tabularnewline
-3 & 0.073346044851378 \tabularnewline
-2 & 0.0127645143729394 \tabularnewline
-1 & 0.171746824136192 \tabularnewline
0 & 0.0423903400293619 \tabularnewline
1 & 0.142445353361771 \tabularnewline
2 & 0.187181504683528 \tabularnewline
3 & 0.0521864680892183 \tabularnewline
4 & 0.0423000430012191 \tabularnewline
5 & 0.108513018152896 \tabularnewline
6 & 0.083708822754703 \tabularnewline
7 & 0.0945016168404909 \tabularnewline
8 & 0.132915511748760 \tabularnewline
9 & 0.074696134033715 \tabularnewline
10 & -0.00629687246836543 \tabularnewline
11 & 0.119805664650469 \tabularnewline
12 & 0.0984344220100687 \tabularnewline
13 & 0.127647625620536 \tabularnewline
14 & 0.156844223432599 \tabularnewline
15 & 0.0415697961663499 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6674&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]0.0375218762182277[/C][/ROW]
[ROW][C]-14[/C][C]-0.158191878325947[/C][/ROW]
[ROW][C]-13[/C][C]-0.00605342073586711[/C][/ROW]
[ROW][C]-12[/C][C]0.239326673840961[/C][/ROW]
[ROW][C]-11[/C][C]-0.0407831957348798[/C][/ROW]
[ROW][C]-10[/C][C]0.0791792247422096[/C][/ROW]
[ROW][C]-9[/C][C]0.0584385573803656[/C][/ROW]
[ROW][C]-8[/C][C]-0.0824082444561495[/C][/ROW]
[ROW][C]-7[/C][C]0.14205701808935[/C][/ROW]
[ROW][C]-6[/C][C]0.149321832360581[/C][/ROW]
[ROW][C]-5[/C][C]0.0522205984462898[/C][/ROW]
[ROW][C]-4[/C][C]0.186369739354244[/C][/ROW]
[ROW][C]-3[/C][C]0.073346044851378[/C][/ROW]
[ROW][C]-2[/C][C]0.0127645143729394[/C][/ROW]
[ROW][C]-1[/C][C]0.171746824136192[/C][/ROW]
[ROW][C]0[/C][C]0.0423903400293619[/C][/ROW]
[ROW][C]1[/C][C]0.142445353361771[/C][/ROW]
[ROW][C]2[/C][C]0.187181504683528[/C][/ROW]
[ROW][C]3[/C][C]0.0521864680892183[/C][/ROW]
[ROW][C]4[/C][C]0.0423000430012191[/C][/ROW]
[ROW][C]5[/C][C]0.108513018152896[/C][/ROW]
[ROW][C]6[/C][C]0.083708822754703[/C][/ROW]
[ROW][C]7[/C][C]0.0945016168404909[/C][/ROW]
[ROW][C]8[/C][C]0.132915511748760[/C][/ROW]
[ROW][C]9[/C][C]0.074696134033715[/C][/ROW]
[ROW][C]10[/C][C]-0.00629687246836543[/C][/ROW]
[ROW][C]11[/C][C]0.119805664650469[/C][/ROW]
[ROW][C]12[/C][C]0.0984344220100687[/C][/ROW]
[ROW][C]13[/C][C]0.127647625620536[/C][/ROW]
[ROW][C]14[/C][C]0.156844223432599[/C][/ROW]
[ROW][C]15[/C][C]0.0415697961663499[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6674&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6674&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])
-150.0375218762182277
-14-0.158191878325947
-13-0.00605342073586711
-120.239326673840961
-11-0.0407831957348798
-100.0791792247422096
-90.0584385573803656
-8-0.0824082444561495
-70.14205701808935
-60.149321832360581
-50.0522205984462898
-40.186369739354244
-30.073346044851378
-20.0127645143729394
-10.171746824136192
00.0423903400293619
10.142445353361771
20.187181504683528
30.0521864680892183
40.0423000430012191
50.108513018152896
60.083708822754703
70.0945016168404909
80.132915511748760
90.074696134033715
10-0.00629687246836543
110.119805664650469
120.0984344220100687
130.127647625620536
140.156844223432599
150.0415697961663499


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')