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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 computationThu, 06 Dec 2007 09:00:26 -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/Dec/06/t1196956046lktl6hzn6crk3oc.htm/, Retrieved Fri, 03 May 2024 13:47:25 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2671, Retrieved Fri, 03 May 2024 13:47:25 +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)
-       [Cross Correlation Function] [WS4: Q5 Inflatie ...] [2007-12-06 16:00:26] [9b75aacdafaeee3fe66fbd4de075ccd6] [Current]
-   PD    [Cross Correlation Function] [] [2007-12-21 09:54:36] [74be16979710d4c4e7c6647856088456]
- R PD      [Cross Correlation Function] [cross correlation] [2008-12-13 21:29:04] [c4e82a203a5642d47e013a6c97b9cd86]
-             [Cross Correlation Function] [cross correlatie] [2008-12-16 18:06:18] [c4e82a203a5642d47e013a6c97b9cd86]
-             [Cross Correlation Function] [cross1] [2008-12-16 18:08:44] [c4e82a203a5642d47e013a6c97b9cd86]
-   PD    [Cross Correlation Function] [] [2007-12-21 10:00:11] [74be16979710d4c4e7c6647856088456]
- RMPD      [Univariate Data Series] [Initial data seri...] [2008-12-14 14:02:23] [74be16979710d4c4e7c6647856088456]
- RMPD      [Univariate Data Series] [Initial data seri...] [2008-12-14 14:02:23] [74be16979710d4c4e7c6647856088456]
- RMPD      [Univariate Data Series] [Verschillen in be...] [2008-12-14 14:15:26] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.1
1.3
1.2
1.6
1.7
1.5
0.9
1.5
1.4
1.6
1.7
1.4
1.8
1.7
1.4
1.2
1
1.7
2.4
2
2.1
2
1.8
2.7
2.3
1.9
2
2.3
2.8
2.4
2.3
2.7
2.7
2.9
3
2.2
2.3
2.8
2.8
2.8
2.2
2.6
2.8
2.5
2.4
2.3
1.9
1.7
2
2.1
1.7
1.8
1.8
1.8
1.3
1.3
1.3
1.2
1.4
2.2
Dataseries Y:
Download CSV
Histogram 
733.6
844.9
864.3
833.5
814.9
820.4
710.8
773.1
801.2
832.9
808.3
817.2
745.5
932.6
1057.0
879.9
1089.5
903.0
846.1
959.1
952.0
1092.5
1188.9
996.7
1034.3
898.2
1111.6
900.5
1049.2
1010.9
875.9
849.9
713.4
918.6
912.5
767.0
902.2
891.9
874.0
930.9
944.2
935.9
937.1
885.1
892.4
987.3
946.3
799.6
875.4
846.2
880.6
885.7
868.9
882.5
789.6
773.3
804.3
817.8
836.7
721.8

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2671&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]2 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=2671&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2671&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 time2 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])
-14-0.376665524187462
-13-0.327126881452478
-12-0.231843932468581
-11-0.171566567411992
-10-0.152495300778107
-9-0.0952678108977545
-8-0.0933515893151186
-7-0.0625641278354592
-60.0420957190953198
-50.101237124313121
-40.184170733696904
-30.251370655710161
-20.256349222283128
-10.283868787965933
00.272220466452358
10.278012400114333
20.317251593193890
30.312529462313992
40.362520853159417
50.355518958686624
60.322381942880350
70.345473330085827
80.37077328226824
90.364690533769822
100.353306103020968
110.308384308391399
120.277683934484366
130.272396237197479
140.271336611392712

\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
-14 & -0.376665524187462 \tabularnewline
-13 & -0.327126881452478 \tabularnewline
-12 & -0.231843932468581 \tabularnewline
-11 & -0.171566567411992 \tabularnewline
-10 & -0.152495300778107 \tabularnewline
-9 & -0.0952678108977545 \tabularnewline
-8 & -0.0933515893151186 \tabularnewline
-7 & -0.0625641278354592 \tabularnewline
-6 & 0.0420957190953198 \tabularnewline
-5 & 0.101237124313121 \tabularnewline
-4 & 0.184170733696904 \tabularnewline
-3 & 0.251370655710161 \tabularnewline
-2 & 0.256349222283128 \tabularnewline
-1 & 0.283868787965933 \tabularnewline
0 & 0.272220466452358 \tabularnewline
1 & 0.278012400114333 \tabularnewline
2 & 0.317251593193890 \tabularnewline
3 & 0.312529462313992 \tabularnewline
4 & 0.362520853159417 \tabularnewline
5 & 0.355518958686624 \tabularnewline
6 & 0.322381942880350 \tabularnewline
7 & 0.345473330085827 \tabularnewline
8 & 0.37077328226824 \tabularnewline
9 & 0.364690533769822 \tabularnewline
10 & 0.353306103020968 \tabularnewline
11 & 0.308384308391399 \tabularnewline
12 & 0.277683934484366 \tabularnewline
13 & 0.272396237197479 \tabularnewline
14 & 0.271336611392712 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2671&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]-14[/C][C]-0.376665524187462[/C][/ROW]
[ROW][C]-13[/C][C]-0.327126881452478[/C][/ROW]
[ROW][C]-12[/C][C]-0.231843932468581[/C][/ROW]
[ROW][C]-11[/C][C]-0.171566567411992[/C][/ROW]
[ROW][C]-10[/C][C]-0.152495300778107[/C][/ROW]
[ROW][C]-9[/C][C]-0.0952678108977545[/C][/ROW]
[ROW][C]-8[/C][C]-0.0933515893151186[/C][/ROW]
[ROW][C]-7[/C][C]-0.0625641278354592[/C][/ROW]
[ROW][C]-6[/C][C]0.0420957190953198[/C][/ROW]
[ROW][C]-5[/C][C]0.101237124313121[/C][/ROW]
[ROW][C]-4[/C][C]0.184170733696904[/C][/ROW]
[ROW][C]-3[/C][C]0.251370655710161[/C][/ROW]
[ROW][C]-2[/C][C]0.256349222283128[/C][/ROW]
[ROW][C]-1[/C][C]0.283868787965933[/C][/ROW]
[ROW][C]0[/C][C]0.272220466452358[/C][/ROW]
[ROW][C]1[/C][C]0.278012400114333[/C][/ROW]
[ROW][C]2[/C][C]0.317251593193890[/C][/ROW]
[ROW][C]3[/C][C]0.312529462313992[/C][/ROW]
[ROW][C]4[/C][C]0.362520853159417[/C][/ROW]
[ROW][C]5[/C][C]0.355518958686624[/C][/ROW]
[ROW][C]6[/C][C]0.322381942880350[/C][/ROW]
[ROW][C]7[/C][C]0.345473330085827[/C][/ROW]
[ROW][C]8[/C][C]0.37077328226824[/C][/ROW]
[ROW][C]9[/C][C]0.364690533769822[/C][/ROW]
[ROW][C]10[/C][C]0.353306103020968[/C][/ROW]
[ROW][C]11[/C][C]0.308384308391399[/C][/ROW]
[ROW][C]12[/C][C]0.277683934484366[/C][/ROW]
[ROW][C]13[/C][C]0.272396237197479[/C][/ROW]
[ROW][C]14[/C][C]0.271336611392712[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2671&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2671&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])
-14-0.376665524187462
-13-0.327126881452478
-12-0.231843932468581
-11-0.171566567411992
-10-0.152495300778107
-9-0.0952678108977545
-8-0.0933515893151186
-7-0.0625641278354592
-60.0420957190953198
-50.101237124313121
-40.184170733696904
-30.251370655710161
-20.256349222283128
-10.283868787965933
00.272220466452358
10.278012400114333
20.317251593193890
30.312529462313992
40.362520853159417
50.355518958686624
60.322381942880350
70.345473330085827
80.37077328226824
90.364690533769822
100.353306103020968
110.308384308391399
120.277683934484366
130.272396237197479
140.271336611392712


Figures (Output of Computation)

Input Parameters & R Code

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