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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 computationMon, 01 Dec 2008 12:40:01 -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/2008/Dec/01/t1228160429r5qog496mgqvros.htm/, Retrieved Sun, 05 May 2024 18:24:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27251, Retrieved Sun, 05 May 2024 18:24:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact228

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD  [(Partial) Autocorrelation Function] [Non stationary ti...] [2008-11-28 13:32:29] [a57f5cc542637534b8bb5bcb4d37eab1]
- RMPD    [Cross Correlation Function] [Non stationary ti...] [2008-11-28 13:48:15] [a57f5cc542637534b8bb5bcb4d37eab1]
-   PD        [Cross Correlation Function] [Non stationary ti...] [2008-12-01 19:40:01] [0f30549460cf4ec26d9cf94b1fcf7789] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.33
0.33
0.32
0.33
0.34
0.36
0.34
0.33
0.35
0.31
0.28
0.26
0.26
0.26
0.29
0.30
0.30
0.28
0.29
0.29
0.32
0.33
0.29
0.31
0.33
0.36
0.39
0.30
0.27
0.28
0.29
0.30
0.30
0.30
0.31
0.30
0.31
0.29
0.32
0.33
0.35
0.35
0.36
0.40
0.40
0.47
0.43
0.38
0.38
0.40
0.45
0.47
0.45
0.50
0.54
0.55
0.59
0.51
0.50
0.50
Dataseries Y:
Download CSV
Histogram 
1.00
1.04
1.02
1.07
1.12
1.08
1.02
1.01
1.04
0.98
0.95
0.94
0.94
0.96
0.97
1.03
1.01
0.99
1.00
1.00
1.02
1.01
0.99
0.98
1.01
1.03
1.03
1.00
0.96
0.97
0.98
1.02
1.04
1.01
1.01
1.00
1.01
1.02
1.03
1.06
1.12
1.12
1.13
1.13
1.13
1.17
1.14
1.08
1.07
1.12
1.14
1.21
1.20
1.23
1.29
1.31
1.37
1.35
1.26
1.26

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27251&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27251&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27251&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'George Udny Yule' @ 72.249.76.132






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series2
Degree of seasonal differencing (D) of X series2
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series2
krho(Y[t],X[t+k])
-140.00524382024707728
-130.0442822546758988
-12-0.167586095967622
-110.26569509962989
-10-0.168788793724437
-9-0.0168787504227405
-80.150735110027707
-7-0.283394494018909
-60.341175848304499
-5-0.1933620534909
-4-0.0362347052247089
-30.194968444410206
-2-0.203770591401907
-1-0.0283871889995757
00.333300487002973
1-0.369152574282198
20.192954451540549
3-0.0354098703931000
4-0.188175172596846
50.349129345066402
6-0.219348199029306
7-0.0229873396124320
80.116021527731505
9-0.0779158026198198
10-0.0869569901225923
110.329232486559089
12-0.391467602383048
130.199052523270127
140.0478262357661133

\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 & 2 \tabularnewline
Degree of seasonal differencing (D) of X series & 2 \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 & 2 \tabularnewline
Degree of seasonal differencing (D) of Y series & 2 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & 0.00524382024707728 \tabularnewline
-13 & 0.0442822546758988 \tabularnewline
-12 & -0.167586095967622 \tabularnewline
-11 & 0.26569509962989 \tabularnewline
-10 & -0.168788793724437 \tabularnewline
-9 & -0.0168787504227405 \tabularnewline
-8 & 0.150735110027707 \tabularnewline
-7 & -0.283394494018909 \tabularnewline
-6 & 0.341175848304499 \tabularnewline
-5 & -0.1933620534909 \tabularnewline
-4 & -0.0362347052247089 \tabularnewline
-3 & 0.194968444410206 \tabularnewline
-2 & -0.203770591401907 \tabularnewline
-1 & -0.0283871889995757 \tabularnewline
0 & 0.333300487002973 \tabularnewline
1 & -0.369152574282198 \tabularnewline
2 & 0.192954451540549 \tabularnewline
3 & -0.0354098703931000 \tabularnewline
4 & -0.188175172596846 \tabularnewline
5 & 0.349129345066402 \tabularnewline
6 & -0.219348199029306 \tabularnewline
7 & -0.0229873396124320 \tabularnewline
8 & 0.116021527731505 \tabularnewline
9 & -0.0779158026198198 \tabularnewline
10 & -0.0869569901225923 \tabularnewline
11 & 0.329232486559089 \tabularnewline
12 & -0.391467602383048 \tabularnewline
13 & 0.199052523270127 \tabularnewline
14 & 0.0478262357661133 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27251&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]2[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]2[/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]2[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]2[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-14[/C][C]0.00524382024707728[/C][/ROW]
[ROW][C]-13[/C][C]0.0442822546758988[/C][/ROW]
[ROW][C]-12[/C][C]-0.167586095967622[/C][/ROW]
[ROW][C]-11[/C][C]0.26569509962989[/C][/ROW]
[ROW][C]-10[/C][C]-0.168788793724437[/C][/ROW]
[ROW][C]-9[/C][C]-0.0168787504227405[/C][/ROW]
[ROW][C]-8[/C][C]0.150735110027707[/C][/ROW]
[ROW][C]-7[/C][C]-0.283394494018909[/C][/ROW]
[ROW][C]-6[/C][C]0.341175848304499[/C][/ROW]
[ROW][C]-5[/C][C]-0.1933620534909[/C][/ROW]
[ROW][C]-4[/C][C]-0.0362347052247089[/C][/ROW]
[ROW][C]-3[/C][C]0.194968444410206[/C][/ROW]
[ROW][C]-2[/C][C]-0.203770591401907[/C][/ROW]
[ROW][C]-1[/C][C]-0.0283871889995757[/C][/ROW]
[ROW][C]0[/C][C]0.333300487002973[/C][/ROW]
[ROW][C]1[/C][C]-0.369152574282198[/C][/ROW]
[ROW][C]2[/C][C]0.192954451540549[/C][/ROW]
[ROW][C]3[/C][C]-0.0354098703931000[/C][/ROW]
[ROW][C]4[/C][C]-0.188175172596846[/C][/ROW]
[ROW][C]5[/C][C]0.349129345066402[/C][/ROW]
[ROW][C]6[/C][C]-0.219348199029306[/C][/ROW]
[ROW][C]7[/C][C]-0.0229873396124320[/C][/ROW]
[ROW][C]8[/C][C]0.116021527731505[/C][/ROW]
[ROW][C]9[/C][C]-0.0779158026198198[/C][/ROW]
[ROW][C]10[/C][C]-0.0869569901225923[/C][/ROW]
[ROW][C]11[/C][C]0.329232486559089[/C][/ROW]
[ROW][C]12[/C][C]-0.391467602383048[/C][/ROW]
[ROW][C]13[/C][C]0.199052523270127[/C][/ROW]
[ROW][C]14[/C][C]0.0478262357661133[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27251&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27251&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 series2
Degree of seasonal differencing (D) of X series2
Seasonal Period (s)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series2
Degree of seasonal differencing (D) of Y series2
krho(Y[t],X[t+k])
-140.00524382024707728
-130.0442822546758988
-12-0.167586095967622
-110.26569509962989
-10-0.168788793724437
-9-0.0168787504227405
-80.150735110027707
-7-0.283394494018909
-60.341175848304499
-5-0.1933620534909
-4-0.0362347052247089
-30.194968444410206
-2-0.203770591401907
-1-0.0283871889995757
00.333300487002973
1-0.369152574282198
20.192954451540549
3-0.0354098703931000
4-0.188175172596846
50.349129345066402
6-0.219348199029306
7-0.0229873396124320
80.116021527731505
9-0.0779158026198198
10-0.0869569901225923
110.329232486559089
12-0.391467602383048
130.199052523270127
140.0478262357661133


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = 2 ; par4 = 1 ; par5 = 1 ; par6 = 2 ; par7 = 2 ;
Parameters (R input):
par1 = 1 ; par2 = 2 ; par3 = 2 ; par4 = 1 ; par5 = 1 ; par6 = 2 ; par7 = 2 ;
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')