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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 16:19:51 -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/03/t1228260028rb1n1uapruts0cn.htm/, Retrieved Sun, 19 May 2024 02:42:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28531, Retrieved Sun, 19 May 2024 02:42:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact203

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] [Gilliam Schoorel] [2008-12-02 23:19:51] [4a7b7ae341cb1fe8993cedd56bcfa583] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101,4
100,7
111,7
96,9
101,9
107,2
86,7
92,7
101,4
107,1
100,8
91
96,3
96,7
106,7
104,8
103
105,7
92,4
91
107,7
112
102,1
94,8
99,4
98,7
106,2
103,9
99,5
105,3
93,9
88,3
109,3
112,1
100,3
101,5
96,5
98,8
115,9
106,5
100,7
114,6
97,2
96,8
117,2
112,6
107
106,6
98,9
98,8
110,3
104,4
100,7
117,7
89,1
94,9
112,4
104,9
109,3
104,3
102,3
103,2
118,8
102,6
112,2
116,6
93,6
100
116,4
118,9
114,5
106,2
109,8
107,3
121,9
108,8
111,8
119,8
102,5
103,4
114,4
124,1
115,6
105,2
114,1
115,3
115,8
119,9
112,1
119,7
106,2
101,5
119,3
Dataseries Y:
Download CSV
Histogram 
119,5
125
145
105,3
116,9
120,1
88,9
78,4
114,6
113,3
117
99,6
99,4
101,9
115,2
108,5
113,8
121
92,2
90,2
101,5
126,6
93,9
89,8
93,4
101,5
110,4
105,9
108,4
113,9
86,1
69,4
101,2
100,5
98
106,6
90,1
96,9
125,9
112
100
123,9
79,8
83,4
113,6
112,9
104
109,9
99
106,3
128,9
111,1
102,9
130
87
87,5
117,6
103,4
110,8
112,6
102,5
112,4
135,6
105,1
127,7
137
91
90,5
122,4
123,3
124,3
120
118,1
119
142,7
123,6
129,6
151,6
110,4
99,2
130,5
136,2
129,7
128
121,6
135,8
143,8
147,5
136,2
156,6
123,3
104,5
143,6

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28531&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28531&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28531&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'George Udny Yule' @ 72.249.76.132






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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-16-0.0349271485645077
-15-0.0199090878413811
-140.0562765154947054
-13-0.0390396783088674
-120.0288989583114567
-110.100428983812175
-100.0243311598714335
-90.131940091302448
-80.120109271408236
-7-0.031390568020273
-60.232929352096489
-50.122210702283252
-40.0420039886484575
-30.313719757080582
-20.191575233233498
-10.143420339982031
00.57389618225927
1-0.0214073903227359
20.0762626251671548
30.223544451660855
40.0456358355139876
50.0797036319879022
60.0680485455704961
7-0.0850970578891396
8-0.00944883517610091
90.0216860483299278
10-0.107502180064733
11-0.138005909776794
12-0.0596312905181044
13-0.099563874641913
140.106216278129730
150.00210385379413565
16-0.0656906837951024

\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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & -0.0349271485645077 \tabularnewline
-15 & -0.0199090878413811 \tabularnewline
-14 & 0.0562765154947054 \tabularnewline
-13 & -0.0390396783088674 \tabularnewline
-12 & 0.0288989583114567 \tabularnewline
-11 & 0.100428983812175 \tabularnewline
-10 & 0.0243311598714335 \tabularnewline
-9 & 0.131940091302448 \tabularnewline
-8 & 0.120109271408236 \tabularnewline
-7 & -0.031390568020273 \tabularnewline
-6 & 0.232929352096489 \tabularnewline
-5 & 0.122210702283252 \tabularnewline
-4 & 0.0420039886484575 \tabularnewline
-3 & 0.313719757080582 \tabularnewline
-2 & 0.191575233233498 \tabularnewline
-1 & 0.143420339982031 \tabularnewline
0 & 0.57389618225927 \tabularnewline
1 & -0.0214073903227359 \tabularnewline
2 & 0.0762626251671548 \tabularnewline
3 & 0.223544451660855 \tabularnewline
4 & 0.0456358355139876 \tabularnewline
5 & 0.0797036319879022 \tabularnewline
6 & 0.0680485455704961 \tabularnewline
7 & -0.0850970578891396 \tabularnewline
8 & -0.00944883517610091 \tabularnewline
9 & 0.0216860483299278 \tabularnewline
10 & -0.107502180064733 \tabularnewline
11 & -0.138005909776794 \tabularnewline
12 & -0.0596312905181044 \tabularnewline
13 & -0.099563874641913 \tabularnewline
14 & 0.106216278129730 \tabularnewline
15 & 0.00210385379413565 \tabularnewline
16 & -0.0656906837951024 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28531&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]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]-16[/C][C]-0.0349271485645077[/C][/ROW]
[ROW][C]-15[/C][C]-0.0199090878413811[/C][/ROW]
[ROW][C]-14[/C][C]0.0562765154947054[/C][/ROW]
[ROW][C]-13[/C][C]-0.0390396783088674[/C][/ROW]
[ROW][C]-12[/C][C]0.0288989583114567[/C][/ROW]
[ROW][C]-11[/C][C]0.100428983812175[/C][/ROW]
[ROW][C]-10[/C][C]0.0243311598714335[/C][/ROW]
[ROW][C]-9[/C][C]0.131940091302448[/C][/ROW]
[ROW][C]-8[/C][C]0.120109271408236[/C][/ROW]
[ROW][C]-7[/C][C]-0.031390568020273[/C][/ROW]
[ROW][C]-6[/C][C]0.232929352096489[/C][/ROW]
[ROW][C]-5[/C][C]0.122210702283252[/C][/ROW]
[ROW][C]-4[/C][C]0.0420039886484575[/C][/ROW]
[ROW][C]-3[/C][C]0.313719757080582[/C][/ROW]
[ROW][C]-2[/C][C]0.191575233233498[/C][/ROW]
[ROW][C]-1[/C][C]0.143420339982031[/C][/ROW]
[ROW][C]0[/C][C]0.57389618225927[/C][/ROW]
[ROW][C]1[/C][C]-0.0214073903227359[/C][/ROW]
[ROW][C]2[/C][C]0.0762626251671548[/C][/ROW]
[ROW][C]3[/C][C]0.223544451660855[/C][/ROW]
[ROW][C]4[/C][C]0.0456358355139876[/C][/ROW]
[ROW][C]5[/C][C]0.0797036319879022[/C][/ROW]
[ROW][C]6[/C][C]0.0680485455704961[/C][/ROW]
[ROW][C]7[/C][C]-0.0850970578891396[/C][/ROW]
[ROW][C]8[/C][C]-0.00944883517610091[/C][/ROW]
[ROW][C]9[/C][C]0.0216860483299278[/C][/ROW]
[ROW][C]10[/C][C]-0.107502180064733[/C][/ROW]
[ROW][C]11[/C][C]-0.138005909776794[/C][/ROW]
[ROW][C]12[/C][C]-0.0596312905181044[/C][/ROW]
[ROW][C]13[/C][C]-0.099563874641913[/C][/ROW]
[ROW][C]14[/C][C]0.106216278129730[/C][/ROW]
[ROW][C]15[/C][C]0.00210385379413565[/C][/ROW]
[ROW][C]16[/C][C]-0.0656906837951024[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28531&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28531&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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-16-0.0349271485645077
-15-0.0199090878413811
-140.0562765154947054
-13-0.0390396783088674
-120.0288989583114567
-110.100428983812175
-100.0243311598714335
-90.131940091302448
-80.120109271408236
-7-0.031390568020273
-60.232929352096489
-50.122210702283252
-40.0420039886484575
-30.313719757080582
-20.191575233233498
-10.143420339982031
00.57389618225927
1-0.0214073903227359
20.0762626251671548
30.223544451660855
40.0456358355139876
50.0797036319879022
60.0680485455704961
7-0.0850970578891396
8-0.00944883517610091
90.0216860483299278
10-0.107502180064733
11-0.138005909776794
12-0.0596312905181044
13-0.099563874641913
140.106216278129730
150.00210385379413565
16-0.0656906837951024


Figures (Output of Computation)

Input Parameters & R Code

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