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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, 18 Dec 2008 02:34:13 -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/18/t1229592898qud8spqak07flh0.htm/, Retrieved Sat, 11 May 2024 17:12:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34613, Retrieved Sat, 11 May 2024 17:12:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact200

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...] [2008-12-13 11:42:49] [b85eb1eb4b13b870c6e7ebbba3e34fcc]
-   P   [Cross Correlation Function] [Cross Correlation...] [2008-12-16 11:55:59] [b85eb1eb4b13b870c6e7ebbba3e34fcc]
-   PD      [Cross Correlation Function] [Cross Correlation] [2008-12-18 09:34:13] [b5110a3ab194da7214bdf478e0a05dbd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
85.0
95.9
108.9
96.2
100.1
105.7
64.5
66.8
110.3
96.1
102.5
97.6
83.6
86.5
96.0
91.1
87.2
84.5
59.2
61.5
98.8
97.9
92.7
84.2
74.5
79.7
86.8
79.8
87.0
91.4
58.7
62.8
87.9
90.4
80.6
73.5
71.4
70.6
78.3
76.0
77.4
80.9
63.4
58.1
88.2
81.2
84.9
76.4
71.5
76.1
82.9
78.0
82.0
84.7
55.7
59.5
83.2
87.6
76.2
76.4
68.3
70.0
76.3
70.9
72.4
80.1
57.4
62.7
82.6
88.9
80.4
72.0
69.4
69.2
77.3
79.4
78.6
76.1
61.8
59.4
78.1
Dataseries Y:
Download CSV
Histogram 
99.5
98.2
108.9
100.0
105.0
108.4
96.7
100.5
115.6
114.9
110.7
107.7
113.5
106.9
119.6
109.4
106.9
118.7
108.9
113.1
125.1
126.5
122.7
127.5
107.1
112.0
122.1
111.5
113.2
128.2
115.1
117.4
132.0
130.8
128.0
132.7
117.0
110.9
123.5
117.4
122.7
123.5
111.5
113.8
131.2
127.0
126.2
121.2
118.8
117.9
135.2
120.7
126.4
129.6
113.4
120.5
135.5
137.6
130.6
133.1
121.5
120.5
136.9
123.7
128.5
135.0
120.9
121.1
132.2
134.5
133.6
136.1
124.5
124.6
133.5
132.3
125.3
135.5
121.2
117.5
135.9

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=34613&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=34613&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34613&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 series1
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
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-15-0.140792921747351
-140.0299155743300132
-13-0.0320700367410776
-120.106620963246760
-11-0.204670100967150
-100.00495176160788638
-90.0850676975763327
-8-0.070750487109127
-7-0.0331538320316298
-60.14787021056666
-50.0763993268145677
-4-0.076226123998949
-30.125912405135505
-2-0.108276173986233
-10.161887041918060
0-0.129465276990655
10.151784036370295
20.0259478796336027
30.0130476596023538
40.133777237107713
50.165352479217701
6-0.192624123855747
7-0.090610433824324
80.00192178763454036
90.0307976343932585
10-0.06794952046406
110.0114635808956732
120.132587481413369
13-0.107313508381481
140.0853111645126073
150.000900118389796023

\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) & 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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & -0.140792921747351 \tabularnewline
-14 & 0.0299155743300132 \tabularnewline
-13 & -0.0320700367410776 \tabularnewline
-12 & 0.106620963246760 \tabularnewline
-11 & -0.204670100967150 \tabularnewline
-10 & 0.00495176160788638 \tabularnewline
-9 & 0.0850676975763327 \tabularnewline
-8 & -0.070750487109127 \tabularnewline
-7 & -0.0331538320316298 \tabularnewline
-6 & 0.14787021056666 \tabularnewline
-5 & 0.0763993268145677 \tabularnewline
-4 & -0.076226123998949 \tabularnewline
-3 & 0.125912405135505 \tabularnewline
-2 & -0.108276173986233 \tabularnewline
-1 & 0.161887041918060 \tabularnewline
0 & -0.129465276990655 \tabularnewline
1 & 0.151784036370295 \tabularnewline
2 & 0.0259478796336027 \tabularnewline
3 & 0.0130476596023538 \tabularnewline
4 & 0.133777237107713 \tabularnewline
5 & 0.165352479217701 \tabularnewline
6 & -0.192624123855747 \tabularnewline
7 & -0.090610433824324 \tabularnewline
8 & 0.00192178763454036 \tabularnewline
9 & 0.0307976343932585 \tabularnewline
10 & -0.06794952046406 \tabularnewline
11 & 0.0114635808956732 \tabularnewline
12 & 0.132587481413369 \tabularnewline
13 & -0.107313508381481 \tabularnewline
14 & 0.0853111645126073 \tabularnewline
15 & 0.000900118389796023 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34613&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]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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]-0.140792921747351[/C][/ROW]
[ROW][C]-14[/C][C]0.0299155743300132[/C][/ROW]
[ROW][C]-13[/C][C]-0.0320700367410776[/C][/ROW]
[ROW][C]-12[/C][C]0.106620963246760[/C][/ROW]
[ROW][C]-11[/C][C]-0.204670100967150[/C][/ROW]
[ROW][C]-10[/C][C]0.00495176160788638[/C][/ROW]
[ROW][C]-9[/C][C]0.0850676975763327[/C][/ROW]
[ROW][C]-8[/C][C]-0.070750487109127[/C][/ROW]
[ROW][C]-7[/C][C]-0.0331538320316298[/C][/ROW]
[ROW][C]-6[/C][C]0.14787021056666[/C][/ROW]
[ROW][C]-5[/C][C]0.0763993268145677[/C][/ROW]
[ROW][C]-4[/C][C]-0.076226123998949[/C][/ROW]
[ROW][C]-3[/C][C]0.125912405135505[/C][/ROW]
[ROW][C]-2[/C][C]-0.108276173986233[/C][/ROW]
[ROW][C]-1[/C][C]0.161887041918060[/C][/ROW]
[ROW][C]0[/C][C]-0.129465276990655[/C][/ROW]
[ROW][C]1[/C][C]0.151784036370295[/C][/ROW]
[ROW][C]2[/C][C]0.0259478796336027[/C][/ROW]
[ROW][C]3[/C][C]0.0130476596023538[/C][/ROW]
[ROW][C]4[/C][C]0.133777237107713[/C][/ROW]
[ROW][C]5[/C][C]0.165352479217701[/C][/ROW]
[ROW][C]6[/C][C]-0.192624123855747[/C][/ROW]
[ROW][C]7[/C][C]-0.090610433824324[/C][/ROW]
[ROW][C]8[/C][C]0.00192178763454036[/C][/ROW]
[ROW][C]9[/C][C]0.0307976343932585[/C][/ROW]
[ROW][C]10[/C][C]-0.06794952046406[/C][/ROW]
[ROW][C]11[/C][C]0.0114635808956732[/C][/ROW]
[ROW][C]12[/C][C]0.132587481413369[/C][/ROW]
[ROW][C]13[/C][C]-0.107313508381481[/C][/ROW]
[ROW][C]14[/C][C]0.0853111645126073[/C][/ROW]
[ROW][C]15[/C][C]0.000900118389796023[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34613&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34613&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)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 series1
krho(Y[t],X[t+k])
-15-0.140792921747351
-140.0299155743300132
-13-0.0320700367410776
-120.106620963246760
-11-0.204670100967150
-100.00495176160788638
-90.0850676975763327
-8-0.070750487109127
-7-0.0331538320316298
-60.14787021056666
-50.0763993268145677
-4-0.076226123998949
-30.125912405135505
-2-0.108276173986233
-10.161887041918060
0-0.129465276990655
10.151784036370295
20.0259478796336027
30.0130476596023538
40.133777237107713
50.165352479217701
6-0.192624123855747
7-0.090610433824324
80.00192178763454036
90.0307976343932585
10-0.06794952046406
110.0114635808956732
120.132587481413369
13-0.107313508381481
140.0853111645126073
150.000900118389796023


Figures (Output of Computation)

Input Parameters & R Code

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