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 computationFri, 19 Dec 2008 16:18:24 -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/20/t12297288284iyz1tblyk3zqec.htm/, Retrieved Sat, 18 May 2024 10:40:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35275, Retrieved Sat, 18 May 2024 10:40:57 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact220

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...] [2008-12-19 23:18:24] [382e90e66f02be5ed86892bdc1574692] [Current]
-    D    [Cross Correlation Function] [Cross Correlatie ...] [2008-12-20 18:22:31] [d32f94eec6fe2d8c421bd223368a5ced]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
74
45
78
98
27
64
20
800
19
85
54
74
63
45
75
800
19
47
59
72
96
66
82
800
54
56
84
89
78
23
45
800
84
54
63
32
54
84
75
800
45
85
63
41
47
86
81
800
Dataseries Y:
Download CSV
Histogram 
75
36
42
78
99
30
44
35
74
45
78
98
27
64
20
800
19
85
54
74
63
45
75
800
19
47
59
72
96
66
82
800
54
56
84
89
78
23
45
800
84
54
63
32
54
84
75
800

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=35275&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=35275&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35275&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)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 series0
krho(Y[t],X[t+k])
-13-0.0974409831720907
-12-0.0924179984954124
-11-0.107413135796678
-10-0.118726530194147
-9-0.130372649694573
-80.900651056687404
-7-0.149759777072275
-6-0.121582820355585
-5-0.111512339012949
-4-0.09877086192608
-3-0.0954210486359296
-2-0.116077137443964
-1-0.107190765338420
00.888348931466909
1-0.121445083720952
2-0.122404896167826
3-0.0855369691564026
4-0.0914804519503486
5-0.100947219296782
6-0.124447361768902
7-0.120993214596292
80.707625037097468
9-0.0892406348097576
10-0.0990753471584752
11-0.06063482356604
12-0.0651237775504317
13-0.0887215468382657

\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) & 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 & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.0974409831720907 \tabularnewline
-12 & -0.0924179984954124 \tabularnewline
-11 & -0.107413135796678 \tabularnewline
-10 & -0.118726530194147 \tabularnewline
-9 & -0.130372649694573 \tabularnewline
-8 & 0.900651056687404 \tabularnewline
-7 & -0.149759777072275 \tabularnewline
-6 & -0.121582820355585 \tabularnewline
-5 & -0.111512339012949 \tabularnewline
-4 & -0.09877086192608 \tabularnewline
-3 & -0.0954210486359296 \tabularnewline
-2 & -0.116077137443964 \tabularnewline
-1 & -0.107190765338420 \tabularnewline
0 & 0.888348931466909 \tabularnewline
1 & -0.121445083720952 \tabularnewline
2 & -0.122404896167826 \tabularnewline
3 & -0.0855369691564026 \tabularnewline
4 & -0.0914804519503486 \tabularnewline
5 & -0.100947219296782 \tabularnewline
6 & -0.124447361768902 \tabularnewline
7 & -0.120993214596292 \tabularnewline
8 & 0.707625037097468 \tabularnewline
9 & -0.0892406348097576 \tabularnewline
10 & -0.0990753471584752 \tabularnewline
11 & -0.06063482356604 \tabularnewline
12 & -0.0651237775504317 \tabularnewline
13 & -0.0887215468382657 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35275&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]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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]-0.0974409831720907[/C][/ROW]
[ROW][C]-12[/C][C]-0.0924179984954124[/C][/ROW]
[ROW][C]-11[/C][C]-0.107413135796678[/C][/ROW]
[ROW][C]-10[/C][C]-0.118726530194147[/C][/ROW]
[ROW][C]-9[/C][C]-0.130372649694573[/C][/ROW]
[ROW][C]-8[/C][C]0.900651056687404[/C][/ROW]
[ROW][C]-7[/C][C]-0.149759777072275[/C][/ROW]
[ROW][C]-6[/C][C]-0.121582820355585[/C][/ROW]
[ROW][C]-5[/C][C]-0.111512339012949[/C][/ROW]
[ROW][C]-4[/C][C]-0.09877086192608[/C][/ROW]
[ROW][C]-3[/C][C]-0.0954210486359296[/C][/ROW]
[ROW][C]-2[/C][C]-0.116077137443964[/C][/ROW]
[ROW][C]-1[/C][C]-0.107190765338420[/C][/ROW]
[ROW][C]0[/C][C]0.888348931466909[/C][/ROW]
[ROW][C]1[/C][C]-0.121445083720952[/C][/ROW]
[ROW][C]2[/C][C]-0.122404896167826[/C][/ROW]
[ROW][C]3[/C][C]-0.0855369691564026[/C][/ROW]
[ROW][C]4[/C][C]-0.0914804519503486[/C][/ROW]
[ROW][C]5[/C][C]-0.100947219296782[/C][/ROW]
[ROW][C]6[/C][C]-0.124447361768902[/C][/ROW]
[ROW][C]7[/C][C]-0.120993214596292[/C][/ROW]
[ROW][C]8[/C][C]0.707625037097468[/C][/ROW]
[ROW][C]9[/C][C]-0.0892406348097576[/C][/ROW]
[ROW][C]10[/C][C]-0.0990753471584752[/C][/ROW]
[ROW][C]11[/C][C]-0.06063482356604[/C][/ROW]
[ROW][C]12[/C][C]-0.0651237775504317[/C][/ROW]
[ROW][C]13[/C][C]-0.0887215468382657[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35275&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35275&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)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 series0
krho(Y[t],X[t+k])
-13-0.0974409831720907
-12-0.0924179984954124
-11-0.107413135796678
-10-0.118726530194147
-9-0.130372649694573
-80.900651056687404
-7-0.149759777072275
-6-0.121582820355585
-5-0.111512339012949
-4-0.09877086192608
-3-0.0954210486359296
-2-0.116077137443964
-1-0.107190765338420
00.888348931466909
1-0.121445083720952
2-0.122404896167826
3-0.0855369691564026
4-0.0914804519503486
5-0.100947219296782
6-0.124447361768902
7-0.120993214596292
80.707625037097468
9-0.0892406348097576
10-0.0990753471584752
11-0.06063482356604
12-0.0651237775504317
13-0.0887215468382657


Figures (Output of Computation)

Input Parameters & R Code

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