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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 computationSun, 25 Nov 2007 07:25:49 -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/Nov/25/t11960002009rhjpmpbf3bcrbd.htm/, Retrieved Sat, 04 May 2024 18:18:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6464, Retrieved Sat, 04 May 2024 18:18:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact174

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] [ws7] [2007-11-25 14:25:49] [e2f7a6e26aa7cf06a3d27eb5298a4843] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
8,1
8,2
8
8,1
8,3
8,2
8,1
7,7
7,6
7,7
8,2
8,4
8,4
8,6
8,4
8,5
8,7
8,7
8,6
7,4
7,3
7,4
9
9,2
9,2
8,5
8,3
8,3
8,6
8,6
8,5
8,1
8,1
8
8,6
8,7
8,7
8,6
8,4
8,4
8,7
8,7
8,5
8,3
8,3
8,3
8,1
8,2
8,1
8,1
7,9
7,7
8,1
8
7,7
7,8
7,6
7,4
7,7
7,9
7,6
Dataseries Y:
Download CSV
Histogram 
7,7
7,8
7,7
7,7
7,7
7,7
7,6
7,5
7,4
7,4
7,5
7,6
7,6
8,1
7,8
8
7,9
7,9
7,8
6,7
6,6
6,6
7,7
7,9
8
7,7
7,5
7,6
7,8
7,8
7,7
7,4
7,5
7,2
7,5
7,6
7,6
7,8
7,7
7,7
8,2
8,2
8,1
7,8
7,8
7,7
6,7
6,7
6,7
7,2
6,9
6,8
7,2
7,1
6,9
6,9
6,7
6,5
6,6
6,6
6,5

Tables (Output of Computation)





Summary of compuational 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 compuational 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=6464&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]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=6464&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6464&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series-2
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 series-1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-130.276349926755379
-120.53497154593196
-110.399735043537848
-100.248276243805809
-90.114046573234478
-80.109182405469103
-70.103428124093300
-60.086574090060634
-50.102572599677007
-40.136680504335648
-30.140337600990697
-2-0.0463128179670558
-1-0.248656060447399
0-0.427000272584039
1-0.262492685587597
2-0.11179617390036
30.0275284601677483
40.0220930699518824
50.0138731992888973
60.00458491180683526
7-0.0363814680545818
8-0.0428842539596698
9-0.0659075238446086
10-0.114916173194960
11-0.148102980855428
12-0.164514388440551
13-0.049789478905823

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & -2 \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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & 0.276349926755379 \tabularnewline
-12 & 0.53497154593196 \tabularnewline
-11 & 0.399735043537848 \tabularnewline
-10 & 0.248276243805809 \tabularnewline
-9 & 0.114046573234478 \tabularnewline
-8 & 0.109182405469103 \tabularnewline
-7 & 0.103428124093300 \tabularnewline
-6 & 0.086574090060634 \tabularnewline
-5 & 0.102572599677007 \tabularnewline
-4 & 0.136680504335648 \tabularnewline
-3 & 0.140337600990697 \tabularnewline
-2 & -0.0463128179670558 \tabularnewline
-1 & -0.248656060447399 \tabularnewline
0 & -0.427000272584039 \tabularnewline
1 & -0.262492685587597 \tabularnewline
2 & -0.11179617390036 \tabularnewline
3 & 0.0275284601677483 \tabularnewline
4 & 0.0220930699518824 \tabularnewline
5 & 0.0138731992888973 \tabularnewline
6 & 0.00458491180683526 \tabularnewline
7 & -0.0363814680545818 \tabularnewline
8 & -0.0428842539596698 \tabularnewline
9 & -0.0659075238446086 \tabularnewline
10 & -0.114916173194960 \tabularnewline
11 & -0.148102980855428 \tabularnewline
12 & -0.164514388440551 \tabularnewline
13 & -0.049789478905823 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6464&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]-2[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]0.276349926755379[/C][/ROW]
[ROW][C]-12[/C][C]0.53497154593196[/C][/ROW]
[ROW][C]-11[/C][C]0.399735043537848[/C][/ROW]
[ROW][C]-10[/C][C]0.248276243805809[/C][/ROW]
[ROW][C]-9[/C][C]0.114046573234478[/C][/ROW]
[ROW][C]-8[/C][C]0.109182405469103[/C][/ROW]
[ROW][C]-7[/C][C]0.103428124093300[/C][/ROW]
[ROW][C]-6[/C][C]0.086574090060634[/C][/ROW]
[ROW][C]-5[/C][C]0.102572599677007[/C][/ROW]
[ROW][C]-4[/C][C]0.136680504335648[/C][/ROW]
[ROW][C]-3[/C][C]0.140337600990697[/C][/ROW]
[ROW][C]-2[/C][C]-0.0463128179670558[/C][/ROW]
[ROW][C]-1[/C][C]-0.248656060447399[/C][/ROW]
[ROW][C]0[/C][C]-0.427000272584039[/C][/ROW]
[ROW][C]1[/C][C]-0.262492685587597[/C][/ROW]
[ROW][C]2[/C][C]-0.11179617390036[/C][/ROW]
[ROW][C]3[/C][C]0.0275284601677483[/C][/ROW]
[ROW][C]4[/C][C]0.0220930699518824[/C][/ROW]
[ROW][C]5[/C][C]0.0138731992888973[/C][/ROW]
[ROW][C]6[/C][C]0.00458491180683526[/C][/ROW]
[ROW][C]7[/C][C]-0.0363814680545818[/C][/ROW]
[ROW][C]8[/C][C]-0.0428842539596698[/C][/ROW]
[ROW][C]9[/C][C]-0.0659075238446086[/C][/ROW]
[ROW][C]10[/C][C]-0.114916173194960[/C][/ROW]
[ROW][C]11[/C][C]-0.148102980855428[/C][/ROW]
[ROW][C]12[/C][C]-0.164514388440551[/C][/ROW]
[ROW][C]13[/C][C]-0.049789478905823[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6464&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6464&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 series-2
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 series-1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-130.276349926755379
-120.53497154593196
-110.399735043537848
-100.248276243805809
-90.114046573234478
-80.109182405469103
-70.103428124093300
-60.086574090060634
-50.102572599677007
-40.136680504335648
-30.140337600990697
-2-0.0463128179670558
-1-0.248656060447399
0-0.427000272584039
1-0.262492685587597
2-0.11179617390036
30.0275284601677483
40.0220930699518824
50.0138731992888973
60.00458491180683526
7-0.0363814680545818
8-0.0428842539596698
9-0.0659075238446086
10-0.114916173194960
11-0.148102980855428
12-0.164514388440551
13-0.049789478905823


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = -2.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = -1.0 ; par6 = 0 ; par7 = 1 ;
Parameters (R input):
par1 = -2.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = -1.0 ; par6 = 0 ; par7 = 1 ;
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',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')