FreeStatistics.org

Free Statistics

of Irreproducible Research!

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, 09 Dec 2008 11:35:33 -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/09/t1228847932yiprkrdck3kd80k.htm/, Retrieved Sat, 18 May 2024 21:27:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31681, Retrieved Sat, 18 May 2024 21:27:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146

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] [Opdracht 1 - Blok...] [2008-12-09 18:35:33] [1351baa662f198be3bff32f9007a9a6d] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98,1
101,1
111,1
93,3
100
108
70,4
75,4
105,5
112,3
102,5
93,5
86,7
95,2
103,8
97
95,5
101
67,5
64
106,7
100,6
101,2
93,1
84,2
85,8
91,8
92,4
80,3
79,7
62,5
57,1
100,8
100,7
86,2
83,2
71,7
77,5
89,8
80,3
78,7
93,8
57,6
60,6
91
85,3
77,4
77,3
68,3
69,9
81,7
75,1
69,9
84
54,3
60
89,9
77
85,3
77,6
69,2
Dataseries Y:
Download CSV
Histogram 
13
8
7
3
3
4
4
0
-4
-14
-18
-8
-1
1
2
0
1
0
-1
-3
-3
-3
-4
-8
-9
-13
-18
-11
-9
-10
-13
-11
-5
-15
-6
-6
-3
-1
-3
-4
-6
0
-4
-2
-2
-6
-7
-6
-6
-3
-2
-5
-11
-11
-11
-10
-14
-8
-9
-5
-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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31681&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31681&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31681&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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 series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-13-0.130259754309806
-120.00344949995338088
-11-0.0393193204001076
-10-0.113294468947940
-9-0.042942818972975
-80.102081116324171
-70.182837070698178
-6-0.00928290530245537
-50.162497542557609
-40.0638006473071769
-3-0.2317302124166
-20.210958896236323
-1-0.00902881154706269
00.153308742320452
10.0746566963359974
2-0.0544265934712855
3-0.0396835449673707
4-0.1823796817803
5-0.0786765381631772
6-0.152859013507853
7-0.226119588462740
80.166734319910184
90.184727067288104
100.0882428337640242
110.0560858461881403
12-0.142513671761292
130.0762130079889194

\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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.130259754309806 \tabularnewline
-12 & 0.00344949995338088 \tabularnewline
-11 & -0.0393193204001076 \tabularnewline
-10 & -0.113294468947940 \tabularnewline
-9 & -0.042942818972975 \tabularnewline
-8 & 0.102081116324171 \tabularnewline
-7 & 0.182837070698178 \tabularnewline
-6 & -0.00928290530245537 \tabularnewline
-5 & 0.162497542557609 \tabularnewline
-4 & 0.0638006473071769 \tabularnewline
-3 & -0.2317302124166 \tabularnewline
-2 & 0.210958896236323 \tabularnewline
-1 & -0.00902881154706269 \tabularnewline
0 & 0.153308742320452 \tabularnewline
1 & 0.0746566963359974 \tabularnewline
2 & -0.0544265934712855 \tabularnewline
3 & -0.0396835449673707 \tabularnewline
4 & -0.1823796817803 \tabularnewline
5 & -0.0786765381631772 \tabularnewline
6 & -0.152859013507853 \tabularnewline
7 & -0.226119588462740 \tabularnewline
8 & 0.166734319910184 \tabularnewline
9 & 0.184727067288104 \tabularnewline
10 & 0.0882428337640242 \tabularnewline
11 & 0.0560858461881403 \tabularnewline
12 & -0.142513671761292 \tabularnewline
13 & 0.0762130079889194 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31681&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]1[/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]-0.130259754309806[/C][/ROW]
[ROW][C]-12[/C][C]0.00344949995338088[/C][/ROW]
[ROW][C]-11[/C][C]-0.0393193204001076[/C][/ROW]
[ROW][C]-10[/C][C]-0.113294468947940[/C][/ROW]
[ROW][C]-9[/C][C]-0.042942818972975[/C][/ROW]
[ROW][C]-8[/C][C]0.102081116324171[/C][/ROW]
[ROW][C]-7[/C][C]0.182837070698178[/C][/ROW]
[ROW][C]-6[/C][C]-0.00928290530245537[/C][/ROW]
[ROW][C]-5[/C][C]0.162497542557609[/C][/ROW]
[ROW][C]-4[/C][C]0.0638006473071769[/C][/ROW]
[ROW][C]-3[/C][C]-0.2317302124166[/C][/ROW]
[ROW][C]-2[/C][C]0.210958896236323[/C][/ROW]
[ROW][C]-1[/C][C]-0.00902881154706269[/C][/ROW]
[ROW][C]0[/C][C]0.153308742320452[/C][/ROW]
[ROW][C]1[/C][C]0.0746566963359974[/C][/ROW]
[ROW][C]2[/C][C]-0.0544265934712855[/C][/ROW]
[ROW][C]3[/C][C]-0.0396835449673707[/C][/ROW]
[ROW][C]4[/C][C]-0.1823796817803[/C][/ROW]
[ROW][C]5[/C][C]-0.0786765381631772[/C][/ROW]
[ROW][C]6[/C][C]-0.152859013507853[/C][/ROW]
[ROW][C]7[/C][C]-0.226119588462740[/C][/ROW]
[ROW][C]8[/C][C]0.166734319910184[/C][/ROW]
[ROW][C]9[/C][C]0.184727067288104[/C][/ROW]
[ROW][C]10[/C][C]0.0882428337640242[/C][/ROW]
[ROW][C]11[/C][C]0.0560858461881403[/C][/ROW]
[ROW][C]12[/C][C]-0.142513671761292[/C][/ROW]
[ROW][C]13[/C][C]0.0762130079889194[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31681&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31681&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 series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-13-0.130259754309806
-120.00344949995338088
-11-0.0393193204001076
-10-0.113294468947940
-9-0.042942818972975
-80.102081116324171
-70.182837070698178
-6-0.00928290530245537
-50.162497542557609
-40.0638006473071769
-3-0.2317302124166
-20.210958896236323
-1-0.00902881154706269
00.153308742320452
10.0746566963359974
2-0.0544265934712855
3-0.0396835449673707
4-0.1823796817803
5-0.0786765381631772
6-0.152859013507853
7-0.226119588462740
80.166734319910184
90.184727067288104
100.0882428337640242
110.0560858461881403
12-0.142513671761292
130.0762130079889194


Figures (Output of Computation)

Input Parameters & R Code

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