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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, 18 Dec 2007 06:45:36 -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/2007/Dec/18/t1197984532ffxohe1qh477ezm.htm/, Retrieved Sat, 04 May 2024 06:31:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4512, Retrieved Sat, 04 May 2024 06:31:43 +0000
QR Codes:

Original text written by user:cross correlation, paper met Y: d=0 D=1 X: d=1 D=1
IsPrivate?No (this computation is public)
User-defined keywordscross correlation, paper
Estimated Impact195

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] [workshop paper] [2007-12-18 13:45:36] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99,4
102,7
109,3
93,9
95,3
101,8
85,6
81,1
109,5
104,0
94,5
79,0
92,8
95,6
101,7
90,8
89,5
91,8
83,8
77,4
112,7
98,8
85,7
72,8
96,9
95,0
94,2
87,3
80,6
87,9
79,6
71,9
94,6
91,4
86,6
68,5
90,1
91,6
95,4
85,4
81,6
88,9
84,1
74,7
97,1
95,3
85,1
67,3
80,6
87,9
89,2
81,3
79,7
83,7
82,1
69,3
91,2
85,7
85,2
70,0
85,8
91,4
97,5
87,1
85,1
94,1
85,8
74,7
99,9
90,7
86,8
74,8
91,8
97,6
100,8
85,4
84,0
90,6
80,5
73,9
93,6
Dataseries Y:
Download CSV
Histogram 
101,5
99,2
107,8
92,3
99,2
101,6
87,0
71,4
104,7
115,1
102,5
75,3
96,7
94,6
98,6
99,5
92,0
93,6
89,3
66,9
108,8
113,2
105,5
77,8
102,1
97,0
95,5
99,3
86,4
92,4
85,7
61,9
104,9
107,9
95,6
79,8
94,8
93,7
108,1
96,9
88,8
106,7
86,8
69,8
110,9
105,4
99,2
84,4
87,2
91,9
97,9
94,5
85,0
100,3
78,7
65,8
104,8
96,0
103,3
82,9
91,4
94,5
109,3
92,1
99,3
109,6
87,5
73,1
110,7
111,6
110,7
84,0
101,6
102,1
113,9
99,0
100,4
109,5
93,0
76,8
105,3

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\begin{tabular}{lllllllll}
\hline
Summary of compuational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4512&T=0

[TABLE]
[ROW][C]Summary of compuational 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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4512&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4512&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 compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1
Degree of non-seasonal differencing (d) of X series1
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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.126612092399847
-140.0207437709044604
-130.0605500929718598
-120.179066475737899
-110.0350045320869740
-100.219577920637244
-90.0902731748251948
-8-0.0398369086318309
-70.118910157430046
-60.0350025158050153
-5-0.0672570632874357
-40.0188669015190826
-3-0.0665012486568331
-2-0.119081669672900
-1-0.0194470005725292
0-0.27045396902191
1-0.0819067730834612
20.0214514620435616
3-0.162390411707544
4-0.0696661191163266
50.0152162909835454
6-0.114145500874027
7-0.0530899486123952
80.0990914393729447
90.0130926774552590
10-0.0149748530339110
110.0633204437319011
12-0.0858119776396292
130.0590023068545646
140.081883857286419
15-0.100453444388908

\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 & 1 \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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & 0.126612092399847 \tabularnewline
-14 & 0.0207437709044604 \tabularnewline
-13 & 0.0605500929718598 \tabularnewline
-12 & 0.179066475737899 \tabularnewline
-11 & 0.0350045320869740 \tabularnewline
-10 & 0.219577920637244 \tabularnewline
-9 & 0.0902731748251948 \tabularnewline
-8 & -0.0398369086318309 \tabularnewline
-7 & 0.118910157430046 \tabularnewline
-6 & 0.0350025158050153 \tabularnewline
-5 & -0.0672570632874357 \tabularnewline
-4 & 0.0188669015190826 \tabularnewline
-3 & -0.0665012486568331 \tabularnewline
-2 & -0.119081669672900 \tabularnewline
-1 & -0.0194470005725292 \tabularnewline
0 & -0.27045396902191 \tabularnewline
1 & -0.0819067730834612 \tabularnewline
2 & 0.0214514620435616 \tabularnewline
3 & -0.162390411707544 \tabularnewline
4 & -0.0696661191163266 \tabularnewline
5 & 0.0152162909835454 \tabularnewline
6 & -0.114145500874027 \tabularnewline
7 & -0.0530899486123952 \tabularnewline
8 & 0.0990914393729447 \tabularnewline
9 & 0.0130926774552590 \tabularnewline
10 & -0.0149748530339110 \tabularnewline
11 & 0.0633204437319011 \tabularnewline
12 & -0.0858119776396292 \tabularnewline
13 & 0.0590023068545646 \tabularnewline
14 & 0.081883857286419 \tabularnewline
15 & -0.100453444388908 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4512&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]1[/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]0[/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]0.126612092399847[/C][/ROW]
[ROW][C]-14[/C][C]0.0207437709044604[/C][/ROW]
[ROW][C]-13[/C][C]0.0605500929718598[/C][/ROW]
[ROW][C]-12[/C][C]0.179066475737899[/C][/ROW]
[ROW][C]-11[/C][C]0.0350045320869740[/C][/ROW]
[ROW][C]-10[/C][C]0.219577920637244[/C][/ROW]
[ROW][C]-9[/C][C]0.0902731748251948[/C][/ROW]
[ROW][C]-8[/C][C]-0.0398369086318309[/C][/ROW]
[ROW][C]-7[/C][C]0.118910157430046[/C][/ROW]
[ROW][C]-6[/C][C]0.0350025158050153[/C][/ROW]
[ROW][C]-5[/C][C]-0.0672570632874357[/C][/ROW]
[ROW][C]-4[/C][C]0.0188669015190826[/C][/ROW]
[ROW][C]-3[/C][C]-0.0665012486568331[/C][/ROW]
[ROW][C]-2[/C][C]-0.119081669672900[/C][/ROW]
[ROW][C]-1[/C][C]-0.0194470005725292[/C][/ROW]
[ROW][C]0[/C][C]-0.27045396902191[/C][/ROW]
[ROW][C]1[/C][C]-0.0819067730834612[/C][/ROW]
[ROW][C]2[/C][C]0.0214514620435616[/C][/ROW]
[ROW][C]3[/C][C]-0.162390411707544[/C][/ROW]
[ROW][C]4[/C][C]-0.0696661191163266[/C][/ROW]
[ROW][C]5[/C][C]0.0152162909835454[/C][/ROW]
[ROW][C]6[/C][C]-0.114145500874027[/C][/ROW]
[ROW][C]7[/C][C]-0.0530899486123952[/C][/ROW]
[ROW][C]8[/C][C]0.0990914393729447[/C][/ROW]
[ROW][C]9[/C][C]0.0130926774552590[/C][/ROW]
[ROW][C]10[/C][C]-0.0149748530339110[/C][/ROW]
[ROW][C]11[/C][C]0.0633204437319011[/C][/ROW]
[ROW][C]12[/C][C]-0.0858119776396292[/C][/ROW]
[ROW][C]13[/C][C]0.0590023068545646[/C][/ROW]
[ROW][C]14[/C][C]0.081883857286419[/C][/ROW]
[ROW][C]15[/C][C]-0.100453444388908[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4512&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4512&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 series1
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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.126612092399847
-140.0207437709044604
-130.0605500929718598
-120.179066475737899
-110.0350045320869740
-100.219577920637244
-90.0902731748251948
-8-0.0398369086318309
-70.118910157430046
-60.0350025158050153
-5-0.0672570632874357
-40.0188669015190826
-3-0.0665012486568331
-2-0.119081669672900
-1-0.0194470005725292
0-0.27045396902191
1-0.0819067730834612
20.0214514620435616
3-0.162390411707544
4-0.0696661191163266
50.0152162909835454
6-0.114145500874027
7-0.0530899486123952
80.0990914393729447
90.0130926774552590
10-0.0149748530339110
110.0633204437319011
12-0.0858119776396292
130.0590023068545646
140.081883857286419
15-0.100453444388908


Figures (Output of Computation)

Input Parameters & R Code

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