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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationTue, 02 Dec 2008 06:40:49 -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/t12282252724daqw0jo0v6y3ms.htm/, Retrieved Fri, 17 May 2024 05:01:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27766, Retrieved Fri, 17 May 2024 05:01:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact181

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] [] [2008-12-02 13:40:49] [d41d8cd98f00b204e9800998ecf8427e] [Current]
F   P     [Cross Correlation Function] [] [2008-12-02 13:44:21] [74be16979710d4c4e7c6647856088456]
-   P       [Cross Correlation Function] [] [2008-12-02 13:49:03] [74be16979710d4c4e7c6647856088456]
F   P       [Cross Correlation Function] [] [2008-12-02 13:49:03] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4.56
4.41
4.33
4.20
4.25
4.25
4.19
4.17
4.21
4.21
4.17
4.16
4.19
4.08
4.06
3.98
3.82
3.82
3.72
3.56
3.57
3.49
3.32
3.23
3.04
3.00
2.82
2.73
2.59
2.58
2.53
2.31
2.31
2.30
2.07
2.07
2.06
2.06
2.05
2.05
2.05
2.05
2.05
2.06
2.07
2.08
2.05
2.03
2.02
2.02
2.01
2.01
2.01
2.01
2.01
2.01
2.03
2.04
2.03
2.05
2.08
2.06
2.09
2.19
2.56
2.54
2.63
2.78
2.84
3.02
3.28
3.29
3.29
3.29
3.32
3.34
3.32
3.30
3.30
3.30
3.31
3.35
3.48
3.76
4.06
4.51
4.52
4.53
4.63
4.79
4.77
4.77
4.77
4.81
4.83
4.76
4.61
Dataseries Y:
Download CSV
Histogram 
5.1
4.9
5.2
5.1
4.6
3.7
3.9
3.1
2.8
2.6
2.2
1.8
1.3
1.2
1.4
1.3
1.3
1.9
1.9
2.1
2.0
1.9
1.9
1.9
1.8
1.7
1.6
1.7
1.9
1.7
1.3
2.0
2.0
2.3
2.0
1.7
2.3
2.4
2.4
2.3
2.1
2.1
2.5
2.0
1.8
1.7
1.9
2.1
1.4
1.6
1.7
1.6
1.9
1.6
1.1
1.3
1.6
1.6
1.7
1.6
1.7
1.6
1.5
1.6
1.1
1.5
1.4
1.3
0.9
1.2
0.9
1.1
1.3
1.3
1.4
1.2
1.7
2.0
3.0
3.1
3.2
2.7
2.8
3.0
2.8
3.1
3.1
3.2
3.1
2.7
2.2
2.2
2.1
2.3
2.5
2.3
2.6

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'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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27766&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27766&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27766&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'Gwilym Jenkins' @ 72.249.127.135






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series-0.5
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series0
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])
-160.0409293724707695
-150.0128175297364599
-140.22296384457033
-130.107197121243297
-120.104981128854351
-110.0313728161215304
-100.100762371332138
-90.179434260150752
-80.0957332720151876
-70.0366277684751848
-6-0.0126241660694892
-5-0.0745301551456535
-4-0.0382442183105425
-30.0161020503420928
-20.00642335564547905
-10.0270598473492884
0-0.133352998034452
10.0224832398186509
2-0.0261415480204712
3-0.103348275487084
40.0990415728099319
50.0938058023254248
60.148393625966177
70.161181359844839
80.141766976820315
90.0844890818735361
10-0.0109662896414983
110.113673487954226
120.160920862401312
130.0698347957202994
140.113489945293565
150.0708057367183897
16-0.0543716083399981

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & -0.5 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 1 \tabularnewline
Degree of seasonal differencing (D) of X series & 0 \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
-16 & 0.0409293724707695 \tabularnewline
-15 & 0.0128175297364599 \tabularnewline
-14 & 0.22296384457033 \tabularnewline
-13 & 0.107197121243297 \tabularnewline
-12 & 0.104981128854351 \tabularnewline
-11 & 0.0313728161215304 \tabularnewline
-10 & 0.100762371332138 \tabularnewline
-9 & 0.179434260150752 \tabularnewline
-8 & 0.0957332720151876 \tabularnewline
-7 & 0.0366277684751848 \tabularnewline
-6 & -0.0126241660694892 \tabularnewline
-5 & -0.0745301551456535 \tabularnewline
-4 & -0.0382442183105425 \tabularnewline
-3 & 0.0161020503420928 \tabularnewline
-2 & 0.00642335564547905 \tabularnewline
-1 & 0.0270598473492884 \tabularnewline
0 & -0.133352998034452 \tabularnewline
1 & 0.0224832398186509 \tabularnewline
2 & -0.0261415480204712 \tabularnewline
3 & -0.103348275487084 \tabularnewline
4 & 0.0990415728099319 \tabularnewline
5 & 0.0938058023254248 \tabularnewline
6 & 0.148393625966177 \tabularnewline
7 & 0.161181359844839 \tabularnewline
8 & 0.141766976820315 \tabularnewline
9 & 0.0844890818735361 \tabularnewline
10 & -0.0109662896414983 \tabularnewline
11 & 0.113673487954226 \tabularnewline
12 & 0.160920862401312 \tabularnewline
13 & 0.0698347957202994 \tabularnewline
14 & 0.113489945293565 \tabularnewline
15 & 0.0708057367183897 \tabularnewline
16 & -0.0543716083399981 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27766&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]-0.5[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]0[/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]-16[/C][C]0.0409293724707695[/C][/ROW]
[ROW][C]-15[/C][C]0.0128175297364599[/C][/ROW]
[ROW][C]-14[/C][C]0.22296384457033[/C][/ROW]
[ROW][C]-13[/C][C]0.107197121243297[/C][/ROW]
[ROW][C]-12[/C][C]0.104981128854351[/C][/ROW]
[ROW][C]-11[/C][C]0.0313728161215304[/C][/ROW]
[ROW][C]-10[/C][C]0.100762371332138[/C][/ROW]
[ROW][C]-9[/C][C]0.179434260150752[/C][/ROW]
[ROW][C]-8[/C][C]0.0957332720151876[/C][/ROW]
[ROW][C]-7[/C][C]0.0366277684751848[/C][/ROW]
[ROW][C]-6[/C][C]-0.0126241660694892[/C][/ROW]
[ROW][C]-5[/C][C]-0.0745301551456535[/C][/ROW]
[ROW][C]-4[/C][C]-0.0382442183105425[/C][/ROW]
[ROW][C]-3[/C][C]0.0161020503420928[/C][/ROW]
[ROW][C]-2[/C][C]0.00642335564547905[/C][/ROW]
[ROW][C]-1[/C][C]0.0270598473492884[/C][/ROW]
[ROW][C]0[/C][C]-0.133352998034452[/C][/ROW]
[ROW][C]1[/C][C]0.0224832398186509[/C][/ROW]
[ROW][C]2[/C][C]-0.0261415480204712[/C][/ROW]
[ROW][C]3[/C][C]-0.103348275487084[/C][/ROW]
[ROW][C]4[/C][C]0.0990415728099319[/C][/ROW]
[ROW][C]5[/C][C]0.0938058023254248[/C][/ROW]
[ROW][C]6[/C][C]0.148393625966177[/C][/ROW]
[ROW][C]7[/C][C]0.161181359844839[/C][/ROW]
[ROW][C]8[/C][C]0.141766976820315[/C][/ROW]
[ROW][C]9[/C][C]0.0844890818735361[/C][/ROW]
[ROW][C]10[/C][C]-0.0109662896414983[/C][/ROW]
[ROW][C]11[/C][C]0.113673487954226[/C][/ROW]
[ROW][C]12[/C][C]0.160920862401312[/C][/ROW]
[ROW][C]13[/C][C]0.0698347957202994[/C][/ROW]
[ROW][C]14[/C][C]0.113489945293565[/C][/ROW]
[ROW][C]15[/C][C]0.0708057367183897[/C][/ROW]
[ROW][C]16[/C][C]-0.0543716083399981[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27766&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27766&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 series-0.5
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series0
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])
-160.0409293724707695
-150.0128175297364599
-140.22296384457033
-130.107197121243297
-120.104981128854351
-110.0313728161215304
-100.100762371332138
-90.179434260150752
-80.0957332720151876
-70.0366277684751848
-6-0.0126241660694892
-5-0.0745301551456535
-4-0.0382442183105425
-30.0161020503420928
-20.00642335564547905
-10.0270598473492884
0-0.133352998034452
10.0224832398186509
2-0.0261415480204712
3-0.103348275487084
40.0990415728099319
50.0938058023254248
60.148393625966177
70.161181359844839
80.141766976820315
90.0844890818735361
10-0.0109662896414983
110.113673487954226
120.160920862401312
130.0698347957202994
140.113489945293565
150.0708057367183897
16-0.0543716083399981


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = -0.5 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = -0.5 ; par2 = 1 ; par3 = 0 ; 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')