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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 computationThu, 17 Dec 2009 09:17:08 -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/2009/Dec/17/t12610667154tl3t8n34ytt6oh.htm/, Retrieved Tue, 30 Apr 2024 03:51:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68969, Retrieved Tue, 30 Apr 2024 03:51:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

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] [appelen] [2009-12-17 16:17:08] [5c2088b06970f9a7d6fea063ee8d5871] [Current]
-   P     [Cross Correlation Function] [Appelen kruiscorr...] [2009-12-17 16:28:57] [7773f496f69461f4a67891f0ef752622]
-    D      [Cross Correlation Function] [Seizoenale differ...] [2010-12-02 12:18:28] [ff7c1e95cf99a1dae07ec89975494dde]
- R  D      [Cross Correlation Function] [biefstuk 2 D=1] [2010-12-14 15:11:40] [3df61981e9f4dafed65341be376c4457]
-    D      [Cross Correlation Function] [CCKoffieD1] [2010-12-20 12:46:51] [3fb95cad3bbcce10c72dbbcc5bec5662]
-    D    [Cross Correlation Function] [Appelen Jonagold ...] [2010-12-02 12:14:54] [ff7c1e95cf99a1dae07ec89975494dde]
-    D    [Cross Correlation Function] [boefstuk 2] [2010-12-14 14:59:59] [3df61981e9f4dafed65341be376c4457]
-   PD    [Cross Correlation Function] [cross correlation...] [2010-12-15 15:56:38] [717f3d787904f94c39256c5c1fc72d4c]
-   PD    [Cross Correlation Function] [cross correlation...] [2010-12-15 16:10:46] [717f3d787904f94c39256c5c1fc72d4c]
-   PD    [Cross Correlation Function] [CCKoffie] [2010-12-19 11:41:57] [3fb95cad3bbcce10c72dbbcc5bec5662]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1.19
1.18
1.18
1.33
1.3
1.25
1.22
1.17
1.18
1.19
1.21
1.21
1.2
1.2
1.29
1.83
1.85
1.54
1.52
1.43
1.4
1.4
1.39
1.37
1.33
1.36
1.34
1.75
1.84
1.73
1.63
1.5
1.45
1.38
1.38
1.27
1.31
1.29
1.32
1.48
1.39
1.45
1.44
1.44
1.42
1.39
1.4
1.39
1.3
1.32
1.35
1.51
1.37
1.25
1.15
1.09
1.09
1.06
1.02
1.01
1
1
1.05
1.3
1.34
1.24
1.22
1.06
1
1
1
1.01
Dataseries Y:
Download CSV
Histogram 
1.77
1.76
1.77
1.95
1.98
1.93
1.94
1.92
1.94
1.92
1.92
1.94
1.91
1.88
1.98
2.4
2.47
2.22
1.98
1.89
1.87
1.88
1.86
1.81
1.79
1.78
1.73
1.88
1.91
1.9
1.84
1.85
1.83
1.82
1.82
1.81
1.75
1.74
1.73
1.96
2.07
1.96
1.87
1.84
1.81
1.78
1.72
1.73
1.64
1.61
1.63
1.92
1.88
1.68
1.58
1.49
1.46
1.44
1.44
1.42
1.4
1.38
1.36
1.48
1.56
1.51
1.51
1.42
1.4
1.38
1.35
1.29

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68969&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]0 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68969&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68969&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






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])
-15-0.0536541824943078
-140.0356618710749277
-130.159690672502932
-120.225753501964645
-110.186081466292685
-100.15161997426692
-90.138539256482399
-80.119833436528225
-70.125058578582618
-60.151056530114524
-50.172914200802424
-40.218339278730781
-30.305928141128964
-20.458626357452245
-10.646701186513884
00.745653685603261
10.62482424774063
20.49760913970862
30.423084991249948
40.388310313498021
50.378419755934575
60.378823388320219
70.376338168003039
80.372521545656294
90.389152124812931
100.445745166358638
110.546354040738312
120.604140162129084
130.503634292666874
140.367092025887144
150.254963012626536

\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
-15 & -0.0536541824943078 \tabularnewline
-14 & 0.0356618710749277 \tabularnewline
-13 & 0.159690672502932 \tabularnewline
-12 & 0.225753501964645 \tabularnewline
-11 & 0.186081466292685 \tabularnewline
-10 & 0.15161997426692 \tabularnewline
-9 & 0.138539256482399 \tabularnewline
-8 & 0.119833436528225 \tabularnewline
-7 & 0.125058578582618 \tabularnewline
-6 & 0.151056530114524 \tabularnewline
-5 & 0.172914200802424 \tabularnewline
-4 & 0.218339278730781 \tabularnewline
-3 & 0.305928141128964 \tabularnewline
-2 & 0.458626357452245 \tabularnewline
-1 & 0.646701186513884 \tabularnewline
0 & 0.745653685603261 \tabularnewline
1 & 0.62482424774063 \tabularnewline
2 & 0.49760913970862 \tabularnewline
3 & 0.423084991249948 \tabularnewline
4 & 0.388310313498021 \tabularnewline
5 & 0.378419755934575 \tabularnewline
6 & 0.378823388320219 \tabularnewline
7 & 0.376338168003039 \tabularnewline
8 & 0.372521545656294 \tabularnewline
9 & 0.389152124812931 \tabularnewline
10 & 0.445745166358638 \tabularnewline
11 & 0.546354040738312 \tabularnewline
12 & 0.604140162129084 \tabularnewline
13 & 0.503634292666874 \tabularnewline
14 & 0.367092025887144 \tabularnewline
15 & 0.254963012626536 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68969&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]-15[/C][C]-0.0536541824943078[/C][/ROW]
[ROW][C]-14[/C][C]0.0356618710749277[/C][/ROW]
[ROW][C]-13[/C][C]0.159690672502932[/C][/ROW]
[ROW][C]-12[/C][C]0.225753501964645[/C][/ROW]
[ROW][C]-11[/C][C]0.186081466292685[/C][/ROW]
[ROW][C]-10[/C][C]0.15161997426692[/C][/ROW]
[ROW][C]-9[/C][C]0.138539256482399[/C][/ROW]
[ROW][C]-8[/C][C]0.119833436528225[/C][/ROW]
[ROW][C]-7[/C][C]0.125058578582618[/C][/ROW]
[ROW][C]-6[/C][C]0.151056530114524[/C][/ROW]
[ROW][C]-5[/C][C]0.172914200802424[/C][/ROW]
[ROW][C]-4[/C][C]0.218339278730781[/C][/ROW]
[ROW][C]-3[/C][C]0.305928141128964[/C][/ROW]
[ROW][C]-2[/C][C]0.458626357452245[/C][/ROW]
[ROW][C]-1[/C][C]0.646701186513884[/C][/ROW]
[ROW][C]0[/C][C]0.745653685603261[/C][/ROW]
[ROW][C]1[/C][C]0.62482424774063[/C][/ROW]
[ROW][C]2[/C][C]0.49760913970862[/C][/ROW]
[ROW][C]3[/C][C]0.423084991249948[/C][/ROW]
[ROW][C]4[/C][C]0.388310313498021[/C][/ROW]
[ROW][C]5[/C][C]0.378419755934575[/C][/ROW]
[ROW][C]6[/C][C]0.378823388320219[/C][/ROW]
[ROW][C]7[/C][C]0.376338168003039[/C][/ROW]
[ROW][C]8[/C][C]0.372521545656294[/C][/ROW]
[ROW][C]9[/C][C]0.389152124812931[/C][/ROW]
[ROW][C]10[/C][C]0.445745166358638[/C][/ROW]
[ROW][C]11[/C][C]0.546354040738312[/C][/ROW]
[ROW][C]12[/C][C]0.604140162129084[/C][/ROW]
[ROW][C]13[/C][C]0.503634292666874[/C][/ROW]
[ROW][C]14[/C][C]0.367092025887144[/C][/ROW]
[ROW][C]15[/C][C]0.254963012626536[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68969&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68969&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])
-15-0.0536541824943078
-140.0356618710749277
-130.159690672502932
-120.225753501964645
-110.186081466292685
-100.15161997426692
-90.138539256482399
-80.119833436528225
-70.125058578582618
-60.151056530114524
-50.172914200802424
-40.218339278730781
-30.305928141128964
-20.458626357452245
-10.646701186513884
00.745653685603261
10.62482424774063
20.49760913970862
30.423084991249948
40.388310313498021
50.378419755934575
60.378823388320219
70.376338168003039
80.372521545656294
90.389152124812931
100.445745166358638
110.546354040738312
120.604140162129084
130.503634292666874
140.367092025887144
150.254963012626536


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')