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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, 01 Dec 2008 13:27:56 -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/01/t12281633124tm1zuoowg2b4kc.htm/, Retrieved Sun, 05 May 2024 15:56:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27338, Retrieved Sun, 05 May 2024 15:56:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact237

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]
F RMPD  [Standard Deviation-Mean Plot] [q5 airline data] [2008-11-28 16:40:33] [44a98561a4b3e6ab8cd5a857b48b0914]
F RMP     [(Partial) Autocorrelation Function] [q6 ACF] [2008-11-29 18:07:14] [44a98561a4b3e6ab8cd5a857b48b0914]
- RMPD        [Cross Correlation Function] [Non stationary ti...] [2008-12-01 20:27:56] [07b7cf1321bc38017c2c7efcf91ca696] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
118.3
127.3
112.3
114.9
108.2
105.4
122.1
113.5
110
125.3
114.3
115.6
127.1
123
122.2
126.4
112.7
105.8
120.9
116.3
115.7
127.9
108.3
121.1
128.6
123.1
127.7
126.6
118.4
110
129.6
115.8
125.9
128.4
114
125.6
128.5
136.6
133.1
124.6
123.5
117.2
135.5
124.8
127.8
133.1
125.7
128.4
131.9
146.3
140.6
129.5
132.4
125.9
126.9
135.8
129.5
130.2
133.8
123.3
Dataseries Y:
Download CSV
Histogram 
99.2
99.5
99.7
99.6
100.1
100.3
100.5
100.7
100.9
101.1
101.1
101.1
101.3
100.5
100.3
100
100.1
100.2
100.5
100
100.7
101.2
101.6
101.7
101.5
101.1
101.2
101.1
101.4
101.3
101.6
102
103.2
103.4
103.6
104.8
105.2
105.1
105.1
105.7
106.2
105.9
106.1
106.5
106.7
107.1
107.5
107.9
109.2
110.1
110.2
110.4
110.5
110.8
111.2
111
111.1
111.1
111.1
111.5

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=27338&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=27338&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27338&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 series2
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 series1.7
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-130.275223211858395
-12-0.056831235524831
-110.066634982884
-10-0.0863346281210981
-90.158347990746858
-80.162252735404566
-70.00596814581315893
-60.122655608257394
-50.0407841835343093
-40.132389795485149
-30.0435775166518495
-2-0.03429108121307
-10.237906380186289
0-0.0179370456788062
1-0.00351234541695088
2-0.0281144923447376
30.129763535908110
40.0145435523383054
50.0711321394011952
60.0701673679395497
7-0.0125835110726918
8-0.165723309472387
90.155941578534330
10-0.0282153332961945
11-0.222895601384947
120.0376085977192109
13-0.278255473428008

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 2 \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 & 1.7 \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 & 0.275223211858395 \tabularnewline
-12 & -0.056831235524831 \tabularnewline
-11 & 0.066634982884 \tabularnewline
-10 & -0.0863346281210981 \tabularnewline
-9 & 0.158347990746858 \tabularnewline
-8 & 0.162252735404566 \tabularnewline
-7 & 0.00596814581315893 \tabularnewline
-6 & 0.122655608257394 \tabularnewline
-5 & 0.0407841835343093 \tabularnewline
-4 & 0.132389795485149 \tabularnewline
-3 & 0.0435775166518495 \tabularnewline
-2 & -0.03429108121307 \tabularnewline
-1 & 0.237906380186289 \tabularnewline
0 & -0.0179370456788062 \tabularnewline
1 & -0.00351234541695088 \tabularnewline
2 & -0.0281144923447376 \tabularnewline
3 & 0.129763535908110 \tabularnewline
4 & 0.0145435523383054 \tabularnewline
5 & 0.0711321394011952 \tabularnewline
6 & 0.0701673679395497 \tabularnewline
7 & -0.0125835110726918 \tabularnewline
8 & -0.165723309472387 \tabularnewline
9 & 0.155941578534330 \tabularnewline
10 & -0.0282153332961945 \tabularnewline
11 & -0.222895601384947 \tabularnewline
12 & 0.0376085977192109 \tabularnewline
13 & -0.278255473428008 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27338&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]2[/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]1.7[/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]0.275223211858395[/C][/ROW]
[ROW][C]-12[/C][C]-0.056831235524831[/C][/ROW]
[ROW][C]-11[/C][C]0.066634982884[/C][/ROW]
[ROW][C]-10[/C][C]-0.0863346281210981[/C][/ROW]
[ROW][C]-9[/C][C]0.158347990746858[/C][/ROW]
[ROW][C]-8[/C][C]0.162252735404566[/C][/ROW]
[ROW][C]-7[/C][C]0.00596814581315893[/C][/ROW]
[ROW][C]-6[/C][C]0.122655608257394[/C][/ROW]
[ROW][C]-5[/C][C]0.0407841835343093[/C][/ROW]
[ROW][C]-4[/C][C]0.132389795485149[/C][/ROW]
[ROW][C]-3[/C][C]0.0435775166518495[/C][/ROW]
[ROW][C]-2[/C][C]-0.03429108121307[/C][/ROW]
[ROW][C]-1[/C][C]0.237906380186289[/C][/ROW]
[ROW][C]0[/C][C]-0.0179370456788062[/C][/ROW]
[ROW][C]1[/C][C]-0.00351234541695088[/C][/ROW]
[ROW][C]2[/C][C]-0.0281144923447376[/C][/ROW]
[ROW][C]3[/C][C]0.129763535908110[/C][/ROW]
[ROW][C]4[/C][C]0.0145435523383054[/C][/ROW]
[ROW][C]5[/C][C]0.0711321394011952[/C][/ROW]
[ROW][C]6[/C][C]0.0701673679395497[/C][/ROW]
[ROW][C]7[/C][C]-0.0125835110726918[/C][/ROW]
[ROW][C]8[/C][C]-0.165723309472387[/C][/ROW]
[ROW][C]9[/C][C]0.155941578534330[/C][/ROW]
[ROW][C]10[/C][C]-0.0282153332961945[/C][/ROW]
[ROW][C]11[/C][C]-0.222895601384947[/C][/ROW]
[ROW][C]12[/C][C]0.0376085977192109[/C][/ROW]
[ROW][C]13[/C][C]-0.278255473428008[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27338&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27338&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 series2
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 series1.7
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-130.275223211858395
-12-0.056831235524831
-110.066634982884
-10-0.0863346281210981
-90.158347990746858
-80.162252735404566
-70.00596814581315893
-60.122655608257394
-50.0407841835343093
-40.132389795485149
-30.0435775166518495
-2-0.03429108121307
-10.237906380186289
0-0.0179370456788062
1-0.00351234541695088
2-0.0281144923447376
30.129763535908110
40.0145435523383054
50.0711321394011952
60.0701673679395497
7-0.0125835110726918
8-0.165723309472387
90.155941578534330
10-0.0282153332961945
11-0.222895601384947
120.0376085977192109
13-0.278255473428008


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 1.7 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 2.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 1.7 ; 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')