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, 02 Dec 2008 13:15:37 -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/02/t1228249029ydyo26jy0o5tddr.htm/, Retrieved Fri, 17 May 2024 01:42:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28352, Retrieved Fri, 17 May 2024 01:42:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsCross correlatie eigen tijdsreeks
Estimated Impact131

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [Partial correlati...] [2008-12-02 20:04:35] [12d343c4448a5f9e527bb31caeac580b]
- RMPD    [Cross Correlation Function] [Cross correlatie ...] [2008-12-02 20:15:37] [0cdfeda4aa2f9e551c2e529c44a404df] [Current]
-   PD      [Cross Correlation Function] [Partial correlati...] [2008-12-02 20:18:21] [12d343c4448a5f9e527bb31caeac580b]
- RMPD      [Variance Reduction Matrix] [Variance reductio...] [2008-12-02 20:34:12] [12d343c4448a5f9e527bb31caeac580b]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
119,5
125
145
105,3
116,9
120,1
88,9
78,4
114,6
113,3
117
99,6
99,4
101,9
115,2
108,5
113,8
121
92,2
90,2
101,5
126,6
93,9
89,8
93,4
101,5
110,4
105,9
108,4
113,9
86,1
69,4
101,2
100,5
98
106,6
90,1
96,9
125,9
112
100
123,9
79,8
83,4
113,6
112,9
104
109,9
99
106,3
128,9
111,1
102,9
130
87
87,5
117,6
103,4
110,8
112,6
102,5
112,4
135,6
105,1
127,7
137
91
90,5
122,4
123,3
124,3
120
118,1
119
142,7
123,6
129,6
151,6
110,4
99,2
130,5
136,2
129,7
128
121,6
Dataseries Y:
Download CSV
Histogram 
98,6
98
106,8
96,6
100,1
107,7
91,5
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5
115,7
113,6
129,7
112
116,8
127
112,1
114,2
121,1
131,6
125
120,4
117,7

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28352&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]2 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=28352&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28352&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 time2 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)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-16-0.135971573356830
-150.201019328409401
-14-0.25322242932632
-13-0.250786686983037
-120.604878451538027
-11-0.140215231970619
-10-0.364069035414851
-90.358084899010038
-8-0.167312853623949
-7-0.152843535283431
-60.398083097954479
-5-0.101485089622969
-4-0.182079818132463
-30.386697418387061
-2-0.447857222907553
-1-0.325305704184046
00.835708931204355
1-0.249247384190479
2-0.378130285959829
30.456668998774921
4-0.246704620741285
5-0.193472700843565
60.475615913245751
7-0.19498933002552
8-0.0945690473707055
90.352962236751554
10-0.450404265606447
11-0.217643258506572
120.672820991623278
13-0.235952758889501
14-0.221715934317026
150.326384518805534
16-0.262649170985876

\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) & 1 \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
-16 & -0.135971573356830 \tabularnewline
-15 & 0.201019328409401 \tabularnewline
-14 & -0.25322242932632 \tabularnewline
-13 & -0.250786686983037 \tabularnewline
-12 & 0.604878451538027 \tabularnewline
-11 & -0.140215231970619 \tabularnewline
-10 & -0.364069035414851 \tabularnewline
-9 & 0.358084899010038 \tabularnewline
-8 & -0.167312853623949 \tabularnewline
-7 & -0.152843535283431 \tabularnewline
-6 & 0.398083097954479 \tabularnewline
-5 & -0.101485089622969 \tabularnewline
-4 & -0.182079818132463 \tabularnewline
-3 & 0.386697418387061 \tabularnewline
-2 & -0.447857222907553 \tabularnewline
-1 & -0.325305704184046 \tabularnewline
0 & 0.835708931204355 \tabularnewline
1 & -0.249247384190479 \tabularnewline
2 & -0.378130285959829 \tabularnewline
3 & 0.456668998774921 \tabularnewline
4 & -0.246704620741285 \tabularnewline
5 & -0.193472700843565 \tabularnewline
6 & 0.475615913245751 \tabularnewline
7 & -0.19498933002552 \tabularnewline
8 & -0.0945690473707055 \tabularnewline
9 & 0.352962236751554 \tabularnewline
10 & -0.450404265606447 \tabularnewline
11 & -0.217643258506572 \tabularnewline
12 & 0.672820991623278 \tabularnewline
13 & -0.235952758889501 \tabularnewline
14 & -0.221715934317026 \tabularnewline
15 & 0.326384518805534 \tabularnewline
16 & -0.262649170985876 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28352&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]1[/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]-16[/C][C]-0.135971573356830[/C][/ROW]
[ROW][C]-15[/C][C]0.201019328409401[/C][/ROW]
[ROW][C]-14[/C][C]-0.25322242932632[/C][/ROW]
[ROW][C]-13[/C][C]-0.250786686983037[/C][/ROW]
[ROW][C]-12[/C][C]0.604878451538027[/C][/ROW]
[ROW][C]-11[/C][C]-0.140215231970619[/C][/ROW]
[ROW][C]-10[/C][C]-0.364069035414851[/C][/ROW]
[ROW][C]-9[/C][C]0.358084899010038[/C][/ROW]
[ROW][C]-8[/C][C]-0.167312853623949[/C][/ROW]
[ROW][C]-7[/C][C]-0.152843535283431[/C][/ROW]
[ROW][C]-6[/C][C]0.398083097954479[/C][/ROW]
[ROW][C]-5[/C][C]-0.101485089622969[/C][/ROW]
[ROW][C]-4[/C][C]-0.182079818132463[/C][/ROW]
[ROW][C]-3[/C][C]0.386697418387061[/C][/ROW]
[ROW][C]-2[/C][C]-0.447857222907553[/C][/ROW]
[ROW][C]-1[/C][C]-0.325305704184046[/C][/ROW]
[ROW][C]0[/C][C]0.835708931204355[/C][/ROW]
[ROW][C]1[/C][C]-0.249247384190479[/C][/ROW]
[ROW][C]2[/C][C]-0.378130285959829[/C][/ROW]
[ROW][C]3[/C][C]0.456668998774921[/C][/ROW]
[ROW][C]4[/C][C]-0.246704620741285[/C][/ROW]
[ROW][C]5[/C][C]-0.193472700843565[/C][/ROW]
[ROW][C]6[/C][C]0.475615913245751[/C][/ROW]
[ROW][C]7[/C][C]-0.19498933002552[/C][/ROW]
[ROW][C]8[/C][C]-0.0945690473707055[/C][/ROW]
[ROW][C]9[/C][C]0.352962236751554[/C][/ROW]
[ROW][C]10[/C][C]-0.450404265606447[/C][/ROW]
[ROW][C]11[/C][C]-0.217643258506572[/C][/ROW]
[ROW][C]12[/C][C]0.672820991623278[/C][/ROW]
[ROW][C]13[/C][C]-0.235952758889501[/C][/ROW]
[ROW][C]14[/C][C]-0.221715934317026[/C][/ROW]
[ROW][C]15[/C][C]0.326384518805534[/C][/ROW]
[ROW][C]16[/C][C]-0.262649170985876[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28352&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28352&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)1
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-16-0.135971573356830
-150.201019328409401
-14-0.25322242932632
-13-0.250786686983037
-120.604878451538027
-11-0.140215231970619
-10-0.364069035414851
-90.358084899010038
-8-0.167312853623949
-7-0.152843535283431
-60.398083097954479
-5-0.101485089622969
-4-0.182079818132463
-30.386697418387061
-2-0.447857222907553
-1-0.325305704184046
00.835708931204355
1-0.249247384190479
2-0.378130285959829
30.456668998774921
4-0.246704620741285
5-0.193472700843565
60.475615913245751
7-0.19498933002552
8-0.0945690473707055
90.352962236751554
10-0.450404265606447
11-0.217643258506572
120.672820991623278
13-0.235952758889501
14-0.221715934317026
150.326384518805534
16-0.262649170985876


Figures (Output of Computation)

Input Parameters & R Code

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