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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 computationMon, 08 Dec 2008 13:51:45 -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/08/t12287695590bi037nb7m2r8yn.htm/, Retrieved Tue, 14 May 2024 06:46:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31005, Retrieved Tue, 14 May 2024 06:46:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact235

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] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RM D  [Cross Correlation Function] [Opdracht 1 - Blok...] [2008-11-26 22:16:36] [8094ad203a218aaca2d1cea2c78c2d6e]
F    D    [Cross Correlation Function] [Opdracht 1 - Blok...] [2008-12-02 21:57:15] [8094ad203a218aaca2d1cea2c78c2d6e]
- RM D      [Variance Reduction Matrix] [Opdracht 1 - Blok...] [2008-12-02 22:00:09] [8094ad203a218aaca2d1cea2c78c2d6e]
- RMPD        [Cross Correlation Function] [Opdracht 1 - Blok...] [2008-12-08 17:35:51] [8094ad203a218aaca2d1cea2c78c2d6e]
-   PD            [Cross Correlation Function] [Verbetering Q9 (b...] [2008-12-08 20:51:45] [1351baa662f198be3bff32f9007a9a6d] [Current]
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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=31005&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=31005&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31005&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 series0.1
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])
-13-0.112434807919396
-12-0.0271156148208337
-11-0.0228299492363481
-10-0.112104762031529
-9-0.0339023810744887
-80.0900239217668395
-70.168544813006644
-6-0.0160518351939839
-50.15818505921277
-40.0528409480322666
-3-0.270560902476932
-20.249847291444803
-10.0116663479002904
00.151725467500930
10.0765684812235564
2-0.0652039368068996
3-0.0481912458834464
4-0.192179255293586
5-0.0548160378344533
6-0.160813716860451
7-0.248623905772998
80.138813389518880
90.126693507824168
100.118260032076957
110.0732054763572945
12-0.132171330507632
130.0791965990924859

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0.1 \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 & -0.112434807919396 \tabularnewline
-12 & -0.0271156148208337 \tabularnewline
-11 & -0.0228299492363481 \tabularnewline
-10 & -0.112104762031529 \tabularnewline
-9 & -0.0339023810744887 \tabularnewline
-8 & 0.0900239217668395 \tabularnewline
-7 & 0.168544813006644 \tabularnewline
-6 & -0.0160518351939839 \tabularnewline
-5 & 0.15818505921277 \tabularnewline
-4 & 0.0528409480322666 \tabularnewline
-3 & -0.270560902476932 \tabularnewline
-2 & 0.249847291444803 \tabularnewline
-1 & 0.0116663479002904 \tabularnewline
0 & 0.151725467500930 \tabularnewline
1 & 0.0765684812235564 \tabularnewline
2 & -0.0652039368068996 \tabularnewline
3 & -0.0481912458834464 \tabularnewline
4 & -0.192179255293586 \tabularnewline
5 & -0.0548160378344533 \tabularnewline
6 & -0.160813716860451 \tabularnewline
7 & -0.248623905772998 \tabularnewline
8 & 0.138813389518880 \tabularnewline
9 & 0.126693507824168 \tabularnewline
10 & 0.118260032076957 \tabularnewline
11 & 0.0732054763572945 \tabularnewline
12 & -0.132171330507632 \tabularnewline
13 & 0.0791965990924859 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31005&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]0.1[/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]-0.112434807919396[/C][/ROW]
[ROW][C]-12[/C][C]-0.0271156148208337[/C][/ROW]
[ROW][C]-11[/C][C]-0.0228299492363481[/C][/ROW]
[ROW][C]-10[/C][C]-0.112104762031529[/C][/ROW]
[ROW][C]-9[/C][C]-0.0339023810744887[/C][/ROW]
[ROW][C]-8[/C][C]0.0900239217668395[/C][/ROW]
[ROW][C]-7[/C][C]0.168544813006644[/C][/ROW]
[ROW][C]-6[/C][C]-0.0160518351939839[/C][/ROW]
[ROW][C]-5[/C][C]0.15818505921277[/C][/ROW]
[ROW][C]-4[/C][C]0.0528409480322666[/C][/ROW]
[ROW][C]-3[/C][C]-0.270560902476932[/C][/ROW]
[ROW][C]-2[/C][C]0.249847291444803[/C][/ROW]
[ROW][C]-1[/C][C]0.0116663479002904[/C][/ROW]
[ROW][C]0[/C][C]0.151725467500930[/C][/ROW]
[ROW][C]1[/C][C]0.0765684812235564[/C][/ROW]
[ROW][C]2[/C][C]-0.0652039368068996[/C][/ROW]
[ROW][C]3[/C][C]-0.0481912458834464[/C][/ROW]
[ROW][C]4[/C][C]-0.192179255293586[/C][/ROW]
[ROW][C]5[/C][C]-0.0548160378344533[/C][/ROW]
[ROW][C]6[/C][C]-0.160813716860451[/C][/ROW]
[ROW][C]7[/C][C]-0.248623905772998[/C][/ROW]
[ROW][C]8[/C][C]0.138813389518880[/C][/ROW]
[ROW][C]9[/C][C]0.126693507824168[/C][/ROW]
[ROW][C]10[/C][C]0.118260032076957[/C][/ROW]
[ROW][C]11[/C][C]0.0732054763572945[/C][/ROW]
[ROW][C]12[/C][C]-0.132171330507632[/C][/ROW]
[ROW][C]13[/C][C]0.0791965990924859[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31005&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31005&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 series0.1
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])
-13-0.112434807919396
-12-0.0271156148208337
-11-0.0228299492363481
-10-0.112104762031529
-9-0.0339023810744887
-80.0900239217668395
-70.168544813006644
-6-0.0160518351939839
-50.15818505921277
-40.0528409480322666
-3-0.270560902476932
-20.249847291444803
-10.0116663479002904
00.151725467500930
10.0765684812235564
2-0.0652039368068996
3-0.0481912458834464
4-0.192179255293586
5-0.0548160378344533
6-0.160813716860451
7-0.248623905772998
80.138813389518880
90.126693507824168
100.118260032076957
110.0732054763572945
12-0.132171330507632
130.0791965990924859


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.1 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 0.1 ; 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')