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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 21 Dec 2008 13:30:55 -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/2008/Dec/21/t1229891523cwtbjjok3wqyktl.htm/, Retrieved Sun, 19 May 2024 12:17:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35816, Retrieved Sun, 19 May 2024 12:17:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact160

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Multiple..] [2008-12-09 17:33:14] [f77c9ab3b413812d7baee6b7ec69a15d]
- RMPD    [Cross Correlation Function] [CC] [2008-12-21 20:30:55] [d300b7a0882cee7d84584ad37a3d4ede] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.02
100.67
100.47
100.38
100.33
100.34
100.37
100.39
100.21
100.21
100.22
100.28
100.25
100.25
100.21
100.16
100.18
100.1
99.96
99.88
99.88
99.86
99.84
99.8
99.82
99.81
99.92
100.03
99.99
100.02
100.01
100.13
100.33
100.13
99.96
100.05
99.83
99.8
100.01
100.1
100.13
100.16
100.41
101.34
101.65
101.85
102.07
102.12
102.14
102.21
102.28
102.19
102.33
102.54
102.44
102.78
102.9
103.08
102.77
102.65
102.71
103.29
102.86
103.45
103.72
103.65
103.83
104.45
105.14
105.07
105.31
105.19
105.3
105.02
105.17
105.28
105.45
105.38
105.8
105.96
105.08
105.11
105.61
105.5
Dataseries Y:
Download CSV
Histogram 
101.73
101.63
101.43
101.34
101.01
100.89
100.93
100.77
100.3
99.86
99.71
99.93
99.88
99.92
99.87
99.63
100.05
99.88
100.11
100.05
100.07
100.2
100.21
99.76
99.41
99.24
99.65
99.7
99.79
99.84
101
101.62
101.98
101.46
102.28
102.14
102.02
102.21
101.61
102.38
102.19
102.04
101.76
101.9
102.01
102.37
103.04
103.42
103.76
104.41
104.75
104.28
103.89
104.09
103.8
105.03
105.86
106.04
106.03
106.13
107.21
107.66
108.08
108.76
108.26
108.71
108.65
108.61
108.86
109.54
108.22
108.77
109.9
110.13
109.6
110.42
110.6
109.73
110.72
111.08
111.14
111.01
110.56
111.57

Tables (Output of Computation)





Summary of computational 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 computational 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=35816&T=0

[TABLE]
[ROW][C]Summary of computational 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=35816&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35816&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 computational 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 series1
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 series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-160.0626496456247124
-150.122988257689643
-14-0.0758354898064813
-13-0.0776966596615
-120.209919995828875
-110.0856856733651685
-10-0.0541003142704205
-9-0.132827289889945
-80.236447829848828
-7-0.0291591698153037
-60.0450967859429796
-50.247998593342127
-40.192129025416667
-3-0.0882891892222332
-20.121295955067248
-10.147509860959195
00.113022942090353
10.0341746719542673
2-0.223583218785767
30.152085045015385
40.0424254236527395
5-0.09404726527421
60.184294421398159
70.184540432055786
8-0.0287377505841060
90.0288210461254826
100.170452263167360
110.075088194880425
120.0497668090834069
130.231231986563659
140.0752651159540975
150.0109405037404548
160.0742805361048678

\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 & 1 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & 0.0626496456247124 \tabularnewline
-15 & 0.122988257689643 \tabularnewline
-14 & -0.0758354898064813 \tabularnewline
-13 & -0.0776966596615 \tabularnewline
-12 & 0.209919995828875 \tabularnewline
-11 & 0.0856856733651685 \tabularnewline
-10 & -0.0541003142704205 \tabularnewline
-9 & -0.132827289889945 \tabularnewline
-8 & 0.236447829848828 \tabularnewline
-7 & -0.0291591698153037 \tabularnewline
-6 & 0.0450967859429796 \tabularnewline
-5 & 0.247998593342127 \tabularnewline
-4 & 0.192129025416667 \tabularnewline
-3 & -0.0882891892222332 \tabularnewline
-2 & 0.121295955067248 \tabularnewline
-1 & 0.147509860959195 \tabularnewline
0 & 0.113022942090353 \tabularnewline
1 & 0.0341746719542673 \tabularnewline
2 & -0.223583218785767 \tabularnewline
3 & 0.152085045015385 \tabularnewline
4 & 0.0424254236527395 \tabularnewline
5 & -0.09404726527421 \tabularnewline
6 & 0.184294421398159 \tabularnewline
7 & 0.184540432055786 \tabularnewline
8 & -0.0287377505841060 \tabularnewline
9 & 0.0288210461254826 \tabularnewline
10 & 0.170452263167360 \tabularnewline
11 & 0.075088194880425 \tabularnewline
12 & 0.0497668090834069 \tabularnewline
13 & 0.231231986563659 \tabularnewline
14 & 0.0752651159540975 \tabularnewline
15 & 0.0109405037404548 \tabularnewline
16 & 0.0742805361048678 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35816&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]1[/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]1[/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]0.0626496456247124[/C][/ROW]
[ROW][C]-15[/C][C]0.122988257689643[/C][/ROW]
[ROW][C]-14[/C][C]-0.0758354898064813[/C][/ROW]
[ROW][C]-13[/C][C]-0.0776966596615[/C][/ROW]
[ROW][C]-12[/C][C]0.209919995828875[/C][/ROW]
[ROW][C]-11[/C][C]0.0856856733651685[/C][/ROW]
[ROW][C]-10[/C][C]-0.0541003142704205[/C][/ROW]
[ROW][C]-9[/C][C]-0.132827289889945[/C][/ROW]
[ROW][C]-8[/C][C]0.236447829848828[/C][/ROW]
[ROW][C]-7[/C][C]-0.0291591698153037[/C][/ROW]
[ROW][C]-6[/C][C]0.0450967859429796[/C][/ROW]
[ROW][C]-5[/C][C]0.247998593342127[/C][/ROW]
[ROW][C]-4[/C][C]0.192129025416667[/C][/ROW]
[ROW][C]-3[/C][C]-0.0882891892222332[/C][/ROW]
[ROW][C]-2[/C][C]0.121295955067248[/C][/ROW]
[ROW][C]-1[/C][C]0.147509860959195[/C][/ROW]
[ROW][C]0[/C][C]0.113022942090353[/C][/ROW]
[ROW][C]1[/C][C]0.0341746719542673[/C][/ROW]
[ROW][C]2[/C][C]-0.223583218785767[/C][/ROW]
[ROW][C]3[/C][C]0.152085045015385[/C][/ROW]
[ROW][C]4[/C][C]0.0424254236527395[/C][/ROW]
[ROW][C]5[/C][C]-0.09404726527421[/C][/ROW]
[ROW][C]6[/C][C]0.184294421398159[/C][/ROW]
[ROW][C]7[/C][C]0.184540432055786[/C][/ROW]
[ROW][C]8[/C][C]-0.0287377505841060[/C][/ROW]
[ROW][C]9[/C][C]0.0288210461254826[/C][/ROW]
[ROW][C]10[/C][C]0.170452263167360[/C][/ROW]
[ROW][C]11[/C][C]0.075088194880425[/C][/ROW]
[ROW][C]12[/C][C]0.0497668090834069[/C][/ROW]
[ROW][C]13[/C][C]0.231231986563659[/C][/ROW]
[ROW][C]14[/C][C]0.0752651159540975[/C][/ROW]
[ROW][C]15[/C][C]0.0109405037404548[/C][/ROW]
[ROW][C]16[/C][C]0.0742805361048678[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35816&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35816&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 series1
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 series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-160.0626496456247124
-150.122988257689643
-14-0.0758354898064813
-13-0.0776966596615
-120.209919995828875
-110.0856856733651685
-10-0.0541003142704205
-9-0.132827289889945
-80.236447829848828
-7-0.0291591698153037
-60.0450967859429796
-50.247998593342127
-40.192129025416667
-3-0.0882891892222332
-20.121295955067248
-10.147509860959195
00.113022942090353
10.0341746719542673
2-0.223583218785767
30.152085045015385
40.0424254236527395
5-0.09404726527421
60.184294421398159
70.184540432055786
8-0.0287377505841060
90.0288210461254826
100.170452263167360
110.075088194880425
120.0497668090834069
130.231231986563659
140.0752651159540975
150.0109405037404548
160.0742805361048678


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; 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) y <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',ylab='CCF',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')