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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 computationSat, 11 Dec 2010 15:22:29 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/11/t1292080868gzuj8qkjjjy6krv.htm/, Retrieved Mon, 06 May 2024 11:11:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=108206, Retrieved Mon, 06 May 2024 11:11:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact148

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [Ws4 part 1.1 s090...] [2009-10-27 21:56:53] [e0fc65a5811681d807296d590d5b45de]
-  M D    [Bivariate Explorative Data Analysis] [Paper; bivariate ...] [2009-12-19 19:10:37] [e0fc65a5811681d807296d590d5b45de]
- RMPD      [Cross Correlation Function] [cross correlation...] [2010-12-08 19:50:23] [74be16979710d4c4e7c6647856088456]
-   PD        [Cross Correlation Function] [] [2010-12-09 09:25:48] [b98453cac15ba1066b407e146608df68]
-    D            [Cross Correlation Function] [Cross Correlation...] [2010-12-11 15:22:29] [8eb352cba3cf694c3df89d0a436a2f1b] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
16896.2
16698,00
19691.6
15930.7
17444.6
17699.4
15189.8
15672.7
17180.8
17664.9
17862.9
16162.3
17463.6
16772.1
19106.9
16721.3
18161.3
18509.9
17802.7
16409.9
17967.7
20286.6
19537.3
18021.9
20194.3
19049.6
20244.7
21473.3
19673.6
21053.2
20159.5
18203.6
21289.5
20432.3
17180.4
15816.8
15071.8
14521.1
15668.8
14346.9
13881,00
15465.9
14238.2
13557.7
16127.6
16793.9
16014,00
16867.9
16014.6
15878.6
18664.9
17962.5
17332.7
19542.1
17203.6
Dataseries Y:
Download CSV
Histogram 
16198.9
16554.2
19554.2
15903.8
18003.8
18329.6
16260.7
14851.9
18174.1
18406.6
18466.5
16016.5
17428.5
17167.2
19630,00
17183.6
18344.7
19301.4
18147.5
16192.9
18374.4
20515.2
18957.2
16471.5
18746.8
19009.5
19211.2
20547.7
19325.8
20605.5
20056.9
16141.4
20359.8
19711.6
15638.6
14384.5
13855.6
14308.3
15290.6
14423.8
13779.7
15686.3
14733.8
12522.5
16189.4
16059.1
16007.1
15806.8
15160,00
15692.1
18908.9
16969.9
16997.5
19858.9
17681.2

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=108206&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=108206&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108206&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 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])
-14-0.479534657485722
-13-0.401806158396382
-12-0.183508633517765
-11-0.318964079374741
-10-0.354348184955274
-9-0.167641314604674
-8-0.0220336073114987
-7-0.00528544938364001
-60.203491406941853
-50.233354481764485
-40.337398978145733
-30.472304828717365
-20.390390730778409
-10.553173038685896
00.935339000010779
10.572976482432324
20.484175864551838
30.570256536454365
40.462159112194909
50.388146023593923
60.360324093971957
70.173533484248675
80.155587317169044
90.0112833639687535
10-0.161976167514325
11-0.0971340650693951
120.0378715411513661
13-0.181002206410848
14-0.264532481527079

\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 & -0.479534657485722 \tabularnewline
-13 & -0.401806158396382 \tabularnewline
-12 & -0.183508633517765 \tabularnewline
-11 & -0.318964079374741 \tabularnewline
-10 & -0.354348184955274 \tabularnewline
-9 & -0.167641314604674 \tabularnewline
-8 & -0.0220336073114987 \tabularnewline
-7 & -0.00528544938364001 \tabularnewline
-6 & 0.203491406941853 \tabularnewline
-5 & 0.233354481764485 \tabularnewline
-4 & 0.337398978145733 \tabularnewline
-3 & 0.472304828717365 \tabularnewline
-2 & 0.390390730778409 \tabularnewline
-1 & 0.553173038685896 \tabularnewline
0 & 0.935339000010779 \tabularnewline
1 & 0.572976482432324 \tabularnewline
2 & 0.484175864551838 \tabularnewline
3 & 0.570256536454365 \tabularnewline
4 & 0.462159112194909 \tabularnewline
5 & 0.388146023593923 \tabularnewline
6 & 0.360324093971957 \tabularnewline
7 & 0.173533484248675 \tabularnewline
8 & 0.155587317169044 \tabularnewline
9 & 0.0112833639687535 \tabularnewline
10 & -0.161976167514325 \tabularnewline
11 & -0.0971340650693951 \tabularnewline
12 & 0.0378715411513661 \tabularnewline
13 & -0.181002206410848 \tabularnewline
14 & -0.264532481527079 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=108206&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]-0.479534657485722[/C][/ROW]
[ROW][C]-13[/C][C]-0.401806158396382[/C][/ROW]
[ROW][C]-12[/C][C]-0.183508633517765[/C][/ROW]
[ROW][C]-11[/C][C]-0.318964079374741[/C][/ROW]
[ROW][C]-10[/C][C]-0.354348184955274[/C][/ROW]
[ROW][C]-9[/C][C]-0.167641314604674[/C][/ROW]
[ROW][C]-8[/C][C]-0.0220336073114987[/C][/ROW]
[ROW][C]-7[/C][C]-0.00528544938364001[/C][/ROW]
[ROW][C]-6[/C][C]0.203491406941853[/C][/ROW]
[ROW][C]-5[/C][C]0.233354481764485[/C][/ROW]
[ROW][C]-4[/C][C]0.337398978145733[/C][/ROW]
[ROW][C]-3[/C][C]0.472304828717365[/C][/ROW]
[ROW][C]-2[/C][C]0.390390730778409[/C][/ROW]
[ROW][C]-1[/C][C]0.553173038685896[/C][/ROW]
[ROW][C]0[/C][C]0.935339000010779[/C][/ROW]
[ROW][C]1[/C][C]0.572976482432324[/C][/ROW]
[ROW][C]2[/C][C]0.484175864551838[/C][/ROW]
[ROW][C]3[/C][C]0.570256536454365[/C][/ROW]
[ROW][C]4[/C][C]0.462159112194909[/C][/ROW]
[ROW][C]5[/C][C]0.388146023593923[/C][/ROW]
[ROW][C]6[/C][C]0.360324093971957[/C][/ROW]
[ROW][C]7[/C][C]0.173533484248675[/C][/ROW]
[ROW][C]8[/C][C]0.155587317169044[/C][/ROW]
[ROW][C]9[/C][C]0.0112833639687535[/C][/ROW]
[ROW][C]10[/C][C]-0.161976167514325[/C][/ROW]
[ROW][C]11[/C][C]-0.0971340650693951[/C][/ROW]
[ROW][C]12[/C][C]0.0378715411513661[/C][/ROW]
[ROW][C]13[/C][C]-0.181002206410848[/C][/ROW]
[ROW][C]14[/C][C]-0.264532481527079[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=108206&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=108206&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])
-14-0.479534657485722
-13-0.401806158396382
-12-0.183508633517765
-11-0.318964079374741
-10-0.354348184955274
-9-0.167641314604674
-8-0.0220336073114987
-7-0.00528544938364001
-60.203491406941853
-50.233354481764485
-40.337398978145733
-30.472304828717365
-20.390390730778409
-10.553173038685896
00.935339000010779
10.572976482432324
20.484175864551838
30.570256536454365
40.462159112194909
50.388146023593923
60.360324093971957
70.173533484248675
80.155587317169044
90.0112833639687535
10-0.161976167514325
11-0.0971340650693951
120.0378715411513661
13-0.181002206410848
14-0.264532481527079


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
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) 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')