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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 computationSun, 25 Nov 2007 06:54:12 -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/25/t1195998315nmo8kq8m38cyqaw.htm/, Retrieved Sat, 04 May 2024 14:45:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6450, Retrieved Sat, 04 May 2024 14:45:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWS7CCFMPVSM
Estimated Impact195

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 - CCF - Metal...] [2007-11-25 13:54:12] [e51d7ab0e549b3dc96ac85a81d9bd259] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93,5
94,7
112,9
99,2
105,6
113,0
83,1
81,1
96,9
104,3
97,7
102,6
89,9
96,0
112,7
107,1
106,2
121,0
101,2
83,2
105,1
113,3
99,1
100,3
93,5
98,8
106,2
98,3
102,1
117,1
101,5
80,5
105,9
109,5
97,2
114,5
93,5
100,9
121,1
116,5
109,3
118,1
108,3
105,4
116,2
111,2
105,8
122,7
99,5
107,9
124,6
115,0
110,3
132,7
99,7
96,5
118,7
112,9
130,5
137,9
115,0
116,8
140,9
120,7
134,2
147,3
112,4
107,1
128,4
137,7
135,0
151,0
137,4
132,4
161,3
139,8
146,0
154,6
142,1
120,5
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=6450&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=6450&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6450&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 series0
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 series0
krho(Y[t],X[t+k])
-160.056074115854658
-150.214456928477660
-140.0248087215357243
-130.0749940161699108
-120.497810213593219
-110.335138545857418
-100.116090207043758
-90.238858538905813
-80.172164131070231
-70.217677348215292
-60.565271836895404
-50.402247844725945
-40.281273624740643
-30.470139650216314
-20.219536690518188
-10.290429279956685
00.787824969847527
10.559747576297942
20.329066135540234
30.392521844180755
40.232489554051262
50.250059729487042
60.518707014237347
70.288981258777811
80.161339157735355
90.269434523134050
10-0.0239107778818096
11-0.00425187920972036
120.356211095811607
130.196456534800881
140.0411726861040632
150.0997306402386026
16-0.0341971126376968

\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) & 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 & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & 0.056074115854658 \tabularnewline
-15 & 0.214456928477660 \tabularnewline
-14 & 0.0248087215357243 \tabularnewline
-13 & 0.0749940161699108 \tabularnewline
-12 & 0.497810213593219 \tabularnewline
-11 & 0.335138545857418 \tabularnewline
-10 & 0.116090207043758 \tabularnewline
-9 & 0.238858538905813 \tabularnewline
-8 & 0.172164131070231 \tabularnewline
-7 & 0.217677348215292 \tabularnewline
-6 & 0.565271836895404 \tabularnewline
-5 & 0.402247844725945 \tabularnewline
-4 & 0.281273624740643 \tabularnewline
-3 & 0.470139650216314 \tabularnewline
-2 & 0.219536690518188 \tabularnewline
-1 & 0.290429279956685 \tabularnewline
0 & 0.787824969847527 \tabularnewline
1 & 0.559747576297942 \tabularnewline
2 & 0.329066135540234 \tabularnewline
3 & 0.392521844180755 \tabularnewline
4 & 0.232489554051262 \tabularnewline
5 & 0.250059729487042 \tabularnewline
6 & 0.518707014237347 \tabularnewline
7 & 0.288981258777811 \tabularnewline
8 & 0.161339157735355 \tabularnewline
9 & 0.269434523134050 \tabularnewline
10 & -0.0239107778818096 \tabularnewline
11 & -0.00425187920972036 \tabularnewline
12 & 0.356211095811607 \tabularnewline
13 & 0.196456534800881 \tabularnewline
14 & 0.0411726861040632 \tabularnewline
15 & 0.0997306402386026 \tabularnewline
16 & -0.0341971126376968 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6450&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]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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-16[/C][C]0.056074115854658[/C][/ROW]
[ROW][C]-15[/C][C]0.214456928477660[/C][/ROW]
[ROW][C]-14[/C][C]0.0248087215357243[/C][/ROW]
[ROW][C]-13[/C][C]0.0749940161699108[/C][/ROW]
[ROW][C]-12[/C][C]0.497810213593219[/C][/ROW]
[ROW][C]-11[/C][C]0.335138545857418[/C][/ROW]
[ROW][C]-10[/C][C]0.116090207043758[/C][/ROW]
[ROW][C]-9[/C][C]0.238858538905813[/C][/ROW]
[ROW][C]-8[/C][C]0.172164131070231[/C][/ROW]
[ROW][C]-7[/C][C]0.217677348215292[/C][/ROW]
[ROW][C]-6[/C][C]0.565271836895404[/C][/ROW]
[ROW][C]-5[/C][C]0.402247844725945[/C][/ROW]
[ROW][C]-4[/C][C]0.281273624740643[/C][/ROW]
[ROW][C]-3[/C][C]0.470139650216314[/C][/ROW]
[ROW][C]-2[/C][C]0.219536690518188[/C][/ROW]
[ROW][C]-1[/C][C]0.290429279956685[/C][/ROW]
[ROW][C]0[/C][C]0.787824969847527[/C][/ROW]
[ROW][C]1[/C][C]0.559747576297942[/C][/ROW]
[ROW][C]2[/C][C]0.329066135540234[/C][/ROW]
[ROW][C]3[/C][C]0.392521844180755[/C][/ROW]
[ROW][C]4[/C][C]0.232489554051262[/C][/ROW]
[ROW][C]5[/C][C]0.250059729487042[/C][/ROW]
[ROW][C]6[/C][C]0.518707014237347[/C][/ROW]
[ROW][C]7[/C][C]0.288981258777811[/C][/ROW]
[ROW][C]8[/C][C]0.161339157735355[/C][/ROW]
[ROW][C]9[/C][C]0.269434523134050[/C][/ROW]
[ROW][C]10[/C][C]-0.0239107778818096[/C][/ROW]
[ROW][C]11[/C][C]-0.00425187920972036[/C][/ROW]
[ROW][C]12[/C][C]0.356211095811607[/C][/ROW]
[ROW][C]13[/C][C]0.196456534800881[/C][/ROW]
[ROW][C]14[/C][C]0.0411726861040632[/C][/ROW]
[ROW][C]15[/C][C]0.0997306402386026[/C][/ROW]
[ROW][C]16[/C][C]-0.0341971126376968[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6450&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6450&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)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 series0
krho(Y[t],X[t+k])
-160.056074115854658
-150.214456928477660
-140.0248087215357243
-130.0749940161699108
-120.497810213593219
-110.335138545857418
-100.116090207043758
-90.238858538905813
-80.172164131070231
-70.217677348215292
-60.565271836895404
-50.402247844725945
-40.281273624740643
-30.470139650216314
-20.219536690518188
-10.290429279956685
00.787824969847527
10.559747576297942
20.329066135540234
30.392521844180755
40.232489554051262
50.250059729487042
60.518707014237347
70.288981258777811
80.161339157735355
90.269434523134050
10-0.0239107778818096
11-0.00425187920972036
120.356211095811607
130.196456534800881
140.0411726861040632
150.0997306402386026
16-0.0341971126376968


Figures (Output of Computation)

Input Parameters & R Code

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