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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 computationThu, 18 Dec 2008 06:15:14 -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/18/t1229606245kqtd5t3ocvr2tvg.htm/, Retrieved Sat, 11 May 2024 22:00:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34734, Retrieved Sat, 11 May 2024 22:00:00 +0000
QR Codes:

Original text written by user:in samenwerking met kevin engels stéphanie claes en katrien bourdiaudhy
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact200

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] [blog 1e tijdreeks...] [2008-10-13 19:23:31] [7173087adebe3e3a714c80ea2417b3eb]
-   PD  [Univariate Data Series] [tijdreeksen opnie...] [2008-10-19 17:18:46] [7173087adebe3e3a714c80ea2417b3eb]
- RMP     [Central Tendency] [tijdreeks 2 centr...] [2008-10-19 17:39:42] [7173087adebe3e3a714c80ea2417b3eb]
- RMP       [(Partial) Autocorrelation Function] [ACF aanvragen hyp...] [2008-12-16 14:51:47] [7d3039e6253bb5fb3b26df1537d500b4]
- RMP         [ARIMA Backward Selection] [Arima backward aa...] [2008-12-16 15:38:56] [7d3039e6253bb5fb3b26df1537d500b4]
- RMP           [(Partial) Autocorrelation Function] [acf hypothecair k...] [2008-12-17 15:13:05] [7173087adebe3e3a714c80ea2417b3eb]
- RMP             [ARIMA Backward Selection] [Arima backward se...] [2008-12-17 19:36:16] [7d3039e6253bb5fb3b26df1537d500b4]
-   P               [ARIMA Backward Selection] [Arima aanvragen h...] [2008-12-18 11:08:22] [7d3039e6253bb5fb3b26df1537d500b4]
- RMPD                  [Cross Correlation Function] [cross correlation] [2008-12-18 13:15:14] [95d95b0e883740fcbc85e18ec42dcafb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
5014
6153
6441
5584
6427
6062
5589
6216
5809
4989
6706
7174
6122
8075
6292
6337
8576
6077
5931
6288
7167
6054
6468
6401
6927
7914
7728
8699
8522
6481
7502
7778
7424
6941
8574
9169
7701
9035
7158
8195
8124
7073
7017
7390
7776
6197
6889
7087
6485
7654
6501
6313
7826
6589
6729
5684
8105
6391
5901
6758
Dataseries Y:
Download CSV
Histogram 
2400
4700
3700
2900
2800
3000
3100
3700
3000
2000
1900
1900
1800
3400
3800
2800
3100
2100
2000
2500
2400
2500
3300
3100
3700
5600
3700
2900
4000
2900
2400
3300
3800
4400
4000
3100
2700
5200
4600
3700
3200
2400
2200
3200
3100
2300
2500
2900
2700
5000
3500
3000
3800
2800
2400
2700
2800
2700
2600
3100

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=34734&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=34734&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34734&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 series1
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])
-130.112125628270077
-120.0346654816919402
-110.0935132133157925
-100.250549763133278
-90.047374415925075
-80.00862096241391015
-70.0706763996497906
-60.0686510266284848
-5-0.0236023257534664
-4-0.092766094345928
-3-0.0965635631018827
-2-0.0532523356225016
-1-0.0574080644411202
0-0.129203536529005
1-0.193585973628304
2-0.316052523673156
3-0.323659058316199
4-0.325883712652089
5-0.324383219699941
6-0.342447864620702
7-0.0768153055140445
8-0.174127914805834
9-0.309490745158492
10-0.303246450787696
11-0.247221318876123
12-0.262410145762725
13-0.151372686788304

\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 & 1 \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
-13 & 0.112125628270077 \tabularnewline
-12 & 0.0346654816919402 \tabularnewline
-11 & 0.0935132133157925 \tabularnewline
-10 & 0.250549763133278 \tabularnewline
-9 & 0.047374415925075 \tabularnewline
-8 & 0.00862096241391015 \tabularnewline
-7 & 0.0706763996497906 \tabularnewline
-6 & 0.0686510266284848 \tabularnewline
-5 & -0.0236023257534664 \tabularnewline
-4 & -0.092766094345928 \tabularnewline
-3 & -0.0965635631018827 \tabularnewline
-2 & -0.0532523356225016 \tabularnewline
-1 & -0.0574080644411202 \tabularnewline
0 & -0.129203536529005 \tabularnewline
1 & -0.193585973628304 \tabularnewline
2 & -0.316052523673156 \tabularnewline
3 & -0.323659058316199 \tabularnewline
4 & -0.325883712652089 \tabularnewline
5 & -0.324383219699941 \tabularnewline
6 & -0.342447864620702 \tabularnewline
7 & -0.0768153055140445 \tabularnewline
8 & -0.174127914805834 \tabularnewline
9 & -0.309490745158492 \tabularnewline
10 & -0.303246450787696 \tabularnewline
11 & -0.247221318876123 \tabularnewline
12 & -0.262410145762725 \tabularnewline
13 & -0.151372686788304 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34734&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]1[/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]-13[/C][C]0.112125628270077[/C][/ROW]
[ROW][C]-12[/C][C]0.0346654816919402[/C][/ROW]
[ROW][C]-11[/C][C]0.0935132133157925[/C][/ROW]
[ROW][C]-10[/C][C]0.250549763133278[/C][/ROW]
[ROW][C]-9[/C][C]0.047374415925075[/C][/ROW]
[ROW][C]-8[/C][C]0.00862096241391015[/C][/ROW]
[ROW][C]-7[/C][C]0.0706763996497906[/C][/ROW]
[ROW][C]-6[/C][C]0.0686510266284848[/C][/ROW]
[ROW][C]-5[/C][C]-0.0236023257534664[/C][/ROW]
[ROW][C]-4[/C][C]-0.092766094345928[/C][/ROW]
[ROW][C]-3[/C][C]-0.0965635631018827[/C][/ROW]
[ROW][C]-2[/C][C]-0.0532523356225016[/C][/ROW]
[ROW][C]-1[/C][C]-0.0574080644411202[/C][/ROW]
[ROW][C]0[/C][C]-0.129203536529005[/C][/ROW]
[ROW][C]1[/C][C]-0.193585973628304[/C][/ROW]
[ROW][C]2[/C][C]-0.316052523673156[/C][/ROW]
[ROW][C]3[/C][C]-0.323659058316199[/C][/ROW]
[ROW][C]4[/C][C]-0.325883712652089[/C][/ROW]
[ROW][C]5[/C][C]-0.324383219699941[/C][/ROW]
[ROW][C]6[/C][C]-0.342447864620702[/C][/ROW]
[ROW][C]7[/C][C]-0.0768153055140445[/C][/ROW]
[ROW][C]8[/C][C]-0.174127914805834[/C][/ROW]
[ROW][C]9[/C][C]-0.309490745158492[/C][/ROW]
[ROW][C]10[/C][C]-0.303246450787696[/C][/ROW]
[ROW][C]11[/C][C]-0.247221318876123[/C][/ROW]
[ROW][C]12[/C][C]-0.262410145762725[/C][/ROW]
[ROW][C]13[/C][C]-0.151372686788304[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34734&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34734&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 series1
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])
-130.112125628270077
-120.0346654816919402
-110.0935132133157925
-100.250549763133278
-90.047374415925075
-80.00862096241391015
-70.0706763996497906
-60.0686510266284848
-5-0.0236023257534664
-4-0.092766094345928
-3-0.0965635631018827
-2-0.0532523356225016
-1-0.0574080644411202
0-0.129203536529005
1-0.193585973628304
2-0.316052523673156
3-0.323659058316199
4-0.325883712652089
5-0.324383219699941
6-0.342447864620702
7-0.0768153055140445
8-0.174127914805834
9-0.309490745158492
10-0.303246450787696
11-0.247221318876123
12-0.262410145762725
13-0.151372686788304


Figures (Output of Computation)

Input Parameters & R Code

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