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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 12:55:21 -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/26/t1196106401c3cne3dm5cciav2.htm/, Retrieved Thu, 02 May 2024 20:14:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6653, Retrieved Thu, 02 May 2024 20:14:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact191

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...] [2007-11-26 19:55:21] [db8a46b0d17caf4a2f9ca9845a402581] [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 
93,5
94,7
112,9
99,2
105,6
113
83,1
81,1
96,9
104,3
97,7
102,6
89,9
96
112,7
107,1
106,2
121
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
110,3
132,7
99,7
96,5
118,7
112,9
130,5
137,9
115
116,8
140,9
120,7
134,2
147,3
112,4
107,1
128,4
137,7
135
151
137,4
132,4
161,3
139,8
146
154,6
142,1
120,5

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=6653&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=6653&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6653&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)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])
-16-0.0341971126376968
-150.0997306402386026
-140.0411726861040632
-130.196456534800881
-120.356211095811607
-11-0.00425187920972036
-10-0.0239107778818096
-90.269434523134050
-80.161339157735355
-70.288981258777811
-60.518707014237347
-50.250059729487042
-40.232489554051262
-30.392521844180755
-20.329066135540234
-10.559747576297942
00.787824969847527
10.290429279956685
20.219536690518188
30.470139650216314
40.281273624740643
50.402247844725945
60.565271836895404
70.217677348215292
80.172164131070231
90.238858538905813
100.116090207043758
110.335138545857418
120.497810213593219
130.0749940161699108
140.0248087215357243
150.214456928477660
160.056074115854658

\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
-16 & -0.0341971126376968 \tabularnewline
-15 & 0.0997306402386026 \tabularnewline
-14 & 0.0411726861040632 \tabularnewline
-13 & 0.196456534800881 \tabularnewline
-12 & 0.356211095811607 \tabularnewline
-11 & -0.00425187920972036 \tabularnewline
-10 & -0.0239107778818096 \tabularnewline
-9 & 0.269434523134050 \tabularnewline
-8 & 0.161339157735355 \tabularnewline
-7 & 0.288981258777811 \tabularnewline
-6 & 0.518707014237347 \tabularnewline
-5 & 0.250059729487042 \tabularnewline
-4 & 0.232489554051262 \tabularnewline
-3 & 0.392521844180755 \tabularnewline
-2 & 0.329066135540234 \tabularnewline
-1 & 0.559747576297942 \tabularnewline
0 & 0.787824969847527 \tabularnewline
1 & 0.290429279956685 \tabularnewline
2 & 0.219536690518188 \tabularnewline
3 & 0.470139650216314 \tabularnewline
4 & 0.281273624740643 \tabularnewline
5 & 0.402247844725945 \tabularnewline
6 & 0.565271836895404 \tabularnewline
7 & 0.217677348215292 \tabularnewline
8 & 0.172164131070231 \tabularnewline
9 & 0.238858538905813 \tabularnewline
10 & 0.116090207043758 \tabularnewline
11 & 0.335138545857418 \tabularnewline
12 & 0.497810213593219 \tabularnewline
13 & 0.0749940161699108 \tabularnewline
14 & 0.0248087215357243 \tabularnewline
15 & 0.214456928477660 \tabularnewline
16 & 0.056074115854658 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6653&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]-16[/C][C]-0.0341971126376968[/C][/ROW]
[ROW][C]-15[/C][C]0.0997306402386026[/C][/ROW]
[ROW][C]-14[/C][C]0.0411726861040632[/C][/ROW]
[ROW][C]-13[/C][C]0.196456534800881[/C][/ROW]
[ROW][C]-12[/C][C]0.356211095811607[/C][/ROW]
[ROW][C]-11[/C][C]-0.00425187920972036[/C][/ROW]
[ROW][C]-10[/C][C]-0.0239107778818096[/C][/ROW]
[ROW][C]-9[/C][C]0.269434523134050[/C][/ROW]
[ROW][C]-8[/C][C]0.161339157735355[/C][/ROW]
[ROW][C]-7[/C][C]0.288981258777811[/C][/ROW]
[ROW][C]-6[/C][C]0.518707014237347[/C][/ROW]
[ROW][C]-5[/C][C]0.250059729487042[/C][/ROW]
[ROW][C]-4[/C][C]0.232489554051262[/C][/ROW]
[ROW][C]-3[/C][C]0.392521844180755[/C][/ROW]
[ROW][C]-2[/C][C]0.329066135540234[/C][/ROW]
[ROW][C]-1[/C][C]0.559747576297942[/C][/ROW]
[ROW][C]0[/C][C]0.787824969847527[/C][/ROW]
[ROW][C]1[/C][C]0.290429279956685[/C][/ROW]
[ROW][C]2[/C][C]0.219536690518188[/C][/ROW]
[ROW][C]3[/C][C]0.470139650216314[/C][/ROW]
[ROW][C]4[/C][C]0.281273624740643[/C][/ROW]
[ROW][C]5[/C][C]0.402247844725945[/C][/ROW]
[ROW][C]6[/C][C]0.565271836895404[/C][/ROW]
[ROW][C]7[/C][C]0.217677348215292[/C][/ROW]
[ROW][C]8[/C][C]0.172164131070231[/C][/ROW]
[ROW][C]9[/C][C]0.238858538905813[/C][/ROW]
[ROW][C]10[/C][C]0.116090207043758[/C][/ROW]
[ROW][C]11[/C][C]0.335138545857418[/C][/ROW]
[ROW][C]12[/C][C]0.497810213593219[/C][/ROW]
[ROW][C]13[/C][C]0.0749940161699108[/C][/ROW]
[ROW][C]14[/C][C]0.0248087215357243[/C][/ROW]
[ROW][C]15[/C][C]0.214456928477660[/C][/ROW]
[ROW][C]16[/C][C]0.056074115854658[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6653&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6653&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])
-16-0.0341971126376968
-150.0997306402386026
-140.0411726861040632
-130.196456534800881
-120.356211095811607
-11-0.00425187920972036
-10-0.0239107778818096
-90.269434523134050
-80.161339157735355
-70.288981258777811
-60.518707014237347
-50.250059729487042
-40.232489554051262
-30.392521844180755
-20.329066135540234
-10.559747576297942
00.787824969847527
10.290429279956685
20.219536690518188
30.470139650216314
40.281273624740643
50.402247844725945
60.565271836895404
70.217677348215292
80.172164131070231
90.238858538905813
100.116090207043758
110.335138545857418
120.497810213593219
130.0749940161699108
140.0248087215357243
150.214456928477660
160.056074115854658


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')