FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSat, 24 Nov 2007 07:41:01 -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/24/t1195914731ipo4kaazxymgba5.htm/, Retrieved Fri, 03 May 2024 11:18:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6322, Retrieved Fri, 03 May 2024 11:18:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ5
Estimated Impact200

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] [Inducing Stationa...] [2007-11-24 14:41:01] [3cbd35878d9bd3c68c81c01c5c6ec146] [Current]
Feedback Forum

Post a new message

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 
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=6322&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=6322&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6322&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])
-160.0132612320155673
-150.1874474011995
-140.0494030827740015
-130.218423811403881
-120.438139590253862
-110.0197115350465861
-10-0.0320080633744756
-90.303201743701356
-80.140287021484785
-70.231118826193578
-60.474349992621559
-50.200696213421836
-40.205417162198971
-30.409804518749329
-20.241895976865637
-10.466960454864773
00.799811592261865
10.240309789196282
20.132294075091455
30.458679665860561
40.224682222891838
50.318886284814194
60.561152847301237
70.195698112589316
80.142828067044113
90.282618811422223
100.0842961979124397
110.285433291926112
120.530691811732072
130.0971472121902907
14-0.00141281459410899
150.225120385605681
160.0436001652166831

\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 & 0.0132612320155673 \tabularnewline
-15 & 0.1874474011995 \tabularnewline
-14 & 0.0494030827740015 \tabularnewline
-13 & 0.218423811403881 \tabularnewline
-12 & 0.438139590253862 \tabularnewline
-11 & 0.0197115350465861 \tabularnewline
-10 & -0.0320080633744756 \tabularnewline
-9 & 0.303201743701356 \tabularnewline
-8 & 0.140287021484785 \tabularnewline
-7 & 0.231118826193578 \tabularnewline
-6 & 0.474349992621559 \tabularnewline
-5 & 0.200696213421836 \tabularnewline
-4 & 0.205417162198971 \tabularnewline
-3 & 0.409804518749329 \tabularnewline
-2 & 0.241895976865637 \tabularnewline
-1 & 0.466960454864773 \tabularnewline
0 & 0.799811592261865 \tabularnewline
1 & 0.240309789196282 \tabularnewline
2 & 0.132294075091455 \tabularnewline
3 & 0.458679665860561 \tabularnewline
4 & 0.224682222891838 \tabularnewline
5 & 0.318886284814194 \tabularnewline
6 & 0.561152847301237 \tabularnewline
7 & 0.195698112589316 \tabularnewline
8 & 0.142828067044113 \tabularnewline
9 & 0.282618811422223 \tabularnewline
10 & 0.0842961979124397 \tabularnewline
11 & 0.285433291926112 \tabularnewline
12 & 0.530691811732072 \tabularnewline
13 & 0.0971472121902907 \tabularnewline
14 & -0.00141281459410899 \tabularnewline
15 & 0.225120385605681 \tabularnewline
16 & 0.0436001652166831 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6322&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]0.0132612320155673[/C][/ROW]
[ROW][C]-15[/C][C]0.1874474011995[/C][/ROW]
[ROW][C]-14[/C][C]0.0494030827740015[/C][/ROW]
[ROW][C]-13[/C][C]0.218423811403881[/C][/ROW]
[ROW][C]-12[/C][C]0.438139590253862[/C][/ROW]
[ROW][C]-11[/C][C]0.0197115350465861[/C][/ROW]
[ROW][C]-10[/C][C]-0.0320080633744756[/C][/ROW]
[ROW][C]-9[/C][C]0.303201743701356[/C][/ROW]
[ROW][C]-8[/C][C]0.140287021484785[/C][/ROW]
[ROW][C]-7[/C][C]0.231118826193578[/C][/ROW]
[ROW][C]-6[/C][C]0.474349992621559[/C][/ROW]
[ROW][C]-5[/C][C]0.200696213421836[/C][/ROW]
[ROW][C]-4[/C][C]0.205417162198971[/C][/ROW]
[ROW][C]-3[/C][C]0.409804518749329[/C][/ROW]
[ROW][C]-2[/C][C]0.241895976865637[/C][/ROW]
[ROW][C]-1[/C][C]0.466960454864773[/C][/ROW]
[ROW][C]0[/C][C]0.799811592261865[/C][/ROW]
[ROW][C]1[/C][C]0.240309789196282[/C][/ROW]
[ROW][C]2[/C][C]0.132294075091455[/C][/ROW]
[ROW][C]3[/C][C]0.458679665860561[/C][/ROW]
[ROW][C]4[/C][C]0.224682222891838[/C][/ROW]
[ROW][C]5[/C][C]0.318886284814194[/C][/ROW]
[ROW][C]6[/C][C]0.561152847301237[/C][/ROW]
[ROW][C]7[/C][C]0.195698112589316[/C][/ROW]
[ROW][C]8[/C][C]0.142828067044113[/C][/ROW]
[ROW][C]9[/C][C]0.282618811422223[/C][/ROW]
[ROW][C]10[/C][C]0.0842961979124397[/C][/ROW]
[ROW][C]11[/C][C]0.285433291926112[/C][/ROW]
[ROW][C]12[/C][C]0.530691811732072[/C][/ROW]
[ROW][C]13[/C][C]0.0971472121902907[/C][/ROW]
[ROW][C]14[/C][C]-0.00141281459410899[/C][/ROW]
[ROW][C]15[/C][C]0.225120385605681[/C][/ROW]
[ROW][C]16[/C][C]0.0436001652166831[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6322&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6322&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])
-160.0132612320155673
-150.1874474011995
-140.0494030827740015
-130.218423811403881
-120.438139590253862
-110.0197115350465861
-10-0.0320080633744756
-90.303201743701356
-80.140287021484785
-70.231118826193578
-60.474349992621559
-50.200696213421836
-40.205417162198971
-30.409804518749329
-20.241895976865637
-10.466960454864773
00.799811592261865
10.240309789196282
20.132294075091455
30.458679665860561
40.224682222891838
50.318886284814194
60.561152847301237
70.195698112589316
80.142828067044113
90.282618811422223
100.0842961979124397
110.285433291926112
120.530691811732072
130.0971472121902907
14-0.00141281459410899
150.225120385605681
160.0436001652166831


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = Default ; par2 = 1 ; par3 = 0 ; par4 = 1 ; par5 = 12 ;
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')