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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 computationTue, 23 Dec 2008 11:13:17 -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/23/t1230056026kel3dqv5eot8jkq.htm/, Retrieved Sat, 18 May 2024 14:19:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36370, Retrieved Sat, 18 May 2024 14:19:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

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] [Cross Correlation...] [2007-12-22 13:33:32] [9fd02a4fb76a6860fd38131ad7f5d02f]
- R PD    [Cross Correlation Function] [] [2008-12-23 18:13:17] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
97.5
97.1
97.5
98.5
100.5
102.8
105.2
107.4
108.0
107.6
107.0
105.8
104.3
103.8
104.4
106.2
108.5
109.8
110.3
109.7
108.7
108.9
109.7
110.4
111.4
112.6
113.6
113.8
113.2
113.6
113.9
113.4
113.8
116.0
118.3
120.5
121.9
121.2
120.2
120.6
110.2
109.2
108.7
109.9
112.2
114.5
114.7
113.2
112.1
112.6
113.6
114.0
114.5
115.0
114.9
114.8
114.3
113.7
114.5
116.0
116.6
116.2
115.7
115.6
115.2
115.0
115.7
115.9
115.6
115.9
117.0
117.9
118.8
119.9
Dataseries Y:
Download CSV
Histogram 
104.3
103.9
103.9
103.9
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.0
108.2
112.3
111.3
111.3
115.3
117.2
118.3
118.3
118.3
119.0
120.6
122.6
122.6
127.4
125.9
121.5
118.8
121.6
122.3
122.7
120.8
120.1
120.1
120.1
120.1
128.4
129.8
129.8
128.6
128.6
133.7
130.0
125.9
129.4
129.4
130.6
130.6
130.6
130.8
129.7
125.8
126.0
125.6
125.4
124.7
126.9
129.1

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=36370&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=36370&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36370&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 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])
-150.479296310598718
-140.486327952693519
-130.496500068688682
-120.507043189088047
-110.534562373686748
-100.557886857081597
-90.578606471525812
-80.600282336758324
-70.621502284606799
-60.632830523481254
-50.64109797602104
-40.648940863661648
-30.679968454868763
-20.703848985880835
-10.710740389158211
00.707758831400152
10.640294250834775
20.573109794835723
30.515684364659663
40.46406846519212
50.419805147106986
60.37752964011445
70.337944797723690
80.298258483439355
90.263943612439923
100.240518080833728
110.216914885146647
120.18606665274933
130.159684913705043
140.126064669718199
150.0969439309913067

\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
-15 & 0.479296310598718 \tabularnewline
-14 & 0.486327952693519 \tabularnewline
-13 & 0.496500068688682 \tabularnewline
-12 & 0.507043189088047 \tabularnewline
-11 & 0.534562373686748 \tabularnewline
-10 & 0.557886857081597 \tabularnewline
-9 & 0.578606471525812 \tabularnewline
-8 & 0.600282336758324 \tabularnewline
-7 & 0.621502284606799 \tabularnewline
-6 & 0.632830523481254 \tabularnewline
-5 & 0.64109797602104 \tabularnewline
-4 & 0.648940863661648 \tabularnewline
-3 & 0.679968454868763 \tabularnewline
-2 & 0.703848985880835 \tabularnewline
-1 & 0.710740389158211 \tabularnewline
0 & 0.707758831400152 \tabularnewline
1 & 0.640294250834775 \tabularnewline
2 & 0.573109794835723 \tabularnewline
3 & 0.515684364659663 \tabularnewline
4 & 0.46406846519212 \tabularnewline
5 & 0.419805147106986 \tabularnewline
6 & 0.37752964011445 \tabularnewline
7 & 0.337944797723690 \tabularnewline
8 & 0.298258483439355 \tabularnewline
9 & 0.263943612439923 \tabularnewline
10 & 0.240518080833728 \tabularnewline
11 & 0.216914885146647 \tabularnewline
12 & 0.18606665274933 \tabularnewline
13 & 0.159684913705043 \tabularnewline
14 & 0.126064669718199 \tabularnewline
15 & 0.0969439309913067 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36370&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]-15[/C][C]0.479296310598718[/C][/ROW]
[ROW][C]-14[/C][C]0.486327952693519[/C][/ROW]
[ROW][C]-13[/C][C]0.496500068688682[/C][/ROW]
[ROW][C]-12[/C][C]0.507043189088047[/C][/ROW]
[ROW][C]-11[/C][C]0.534562373686748[/C][/ROW]
[ROW][C]-10[/C][C]0.557886857081597[/C][/ROW]
[ROW][C]-9[/C][C]0.578606471525812[/C][/ROW]
[ROW][C]-8[/C][C]0.600282336758324[/C][/ROW]
[ROW][C]-7[/C][C]0.621502284606799[/C][/ROW]
[ROW][C]-6[/C][C]0.632830523481254[/C][/ROW]
[ROW][C]-5[/C][C]0.64109797602104[/C][/ROW]
[ROW][C]-4[/C][C]0.648940863661648[/C][/ROW]
[ROW][C]-3[/C][C]0.679968454868763[/C][/ROW]
[ROW][C]-2[/C][C]0.703848985880835[/C][/ROW]
[ROW][C]-1[/C][C]0.710740389158211[/C][/ROW]
[ROW][C]0[/C][C]0.707758831400152[/C][/ROW]
[ROW][C]1[/C][C]0.640294250834775[/C][/ROW]
[ROW][C]2[/C][C]0.573109794835723[/C][/ROW]
[ROW][C]3[/C][C]0.515684364659663[/C][/ROW]
[ROW][C]4[/C][C]0.46406846519212[/C][/ROW]
[ROW][C]5[/C][C]0.419805147106986[/C][/ROW]
[ROW][C]6[/C][C]0.37752964011445[/C][/ROW]
[ROW][C]7[/C][C]0.337944797723690[/C][/ROW]
[ROW][C]8[/C][C]0.298258483439355[/C][/ROW]
[ROW][C]9[/C][C]0.263943612439923[/C][/ROW]
[ROW][C]10[/C][C]0.240518080833728[/C][/ROW]
[ROW][C]11[/C][C]0.216914885146647[/C][/ROW]
[ROW][C]12[/C][C]0.18606665274933[/C][/ROW]
[ROW][C]13[/C][C]0.159684913705043[/C][/ROW]
[ROW][C]14[/C][C]0.126064669718199[/C][/ROW]
[ROW][C]15[/C][C]0.0969439309913067[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36370&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36370&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])
-150.479296310598718
-140.486327952693519
-130.496500068688682
-120.507043189088047
-110.534562373686748
-100.557886857081597
-90.578606471525812
-80.600282336758324
-70.621502284606799
-60.632830523481254
-50.64109797602104
-40.648940863661648
-30.679968454868763
-20.703848985880835
-10.710740389158211
00.707758831400152
10.640294250834775
20.573109794835723
30.515684364659663
40.46406846519212
50.419805147106986
60.37752964011445
70.337944797723690
80.298258483439355
90.263943612439923
100.240518080833728
110.216914885146647
120.18606665274933
130.159684913705043
140.126064669718199
150.0969439309913067


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 48 ; 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) 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')