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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 computationThu, 22 Nov 2007 07:28:58 -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/Nov/22/t1195741446w182r29nq4d5scs.htm/, Retrieved Thu, 02 May 2024 14:05:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6020, Retrieved Thu, 02 May 2024 14:05:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ3
Estimated Impact169

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 7] [2007-11-22 14:28:58] [8ce1ad2ac57e06e10fb37a1292ae8cb6] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103,1
100,6
103,1
95,5
90,5
90,9
88,8
90,7
94,3
104,6
111,1
110,8
107,2
99
99
91
96,2
96,9
96,2
100,1
99
115,4
106,9
107,1
99,3
99,2
108,3
105,6
99,5
107,4
93,1
88,1
110,7
113,1
99,6
93,6
98,6
99,6
114,3
107,8
101,2
112,5
100,5
93,9
116,2
112
106,4
95,7
96
95,8
103
102,2
98,4
111,4
86,6
91,3
107,9
101,8
104,4
93,4
100,1
98,5
112,9
101,4
107,1
110,8
90,3
95,5
111,4
113
107,5
95,9
106,3
105,2
117,2
106,9
108,2
110
96,1
100,6
Dataseries Y:
Download CSV
Histogram 
98,6
98
106,8
96,6
100,1
107,7
91,5
97,8
107,4
117,5
105,6
97,4
99,5
98
104,3
100,6
101,1
103,9
96,9
95,5
108,4
117
103,8
100,8
110,6
104
112,6
107,3
98,9
109,8
104,9
102,2
123,9
124,9
112,7
121,9
100,6
104,3
120,4
107,5
102,9
125,6
107,5
108,8
128,4
121,1
119,5
128,7
108,7
105,5
119,8
111,3
110,6
120,1
97,5
107,7
127,3
117,2
119,8
116,2
111
112,4
130,6
109,1
118,8
123,9
101,6
112,8
128
129,6
125,8
119,5
115,7
113,6
129,7
112
116,8
126,3
112,9
115,9

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 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=6020&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]2 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=6020&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6020&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 time2 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 series0
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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t-k])
-16-0.134748297622974
-150.00988659604286463
-140.0245254841084851
-13-0.0262368561627115
-120.401784790241174
-110.131636135333294
-10-0.118406472823555
-90.18104429618926
-80.0458566978802136
-70.0504585721979536
-60.290276400496628
-50.168763695938089
-4-0.0430434545938679
-30.146462960407287
-20.025040364795946
-10.0788012723171934
00.604664328209351
10.192419199243157
2-0.0217236949071001
30.208359812754977
40.0399189158914294
50.119749271209492
60.293395647881458
70.0716124042006511
8-0.0838651402376216
90.0163820823857289
10-0.204153871452882
110.00988137256266165
120.436910351606634
130.0250457800472754
14-0.100073335785255
150.0244495962296422
16-0.0949036323807035

\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 & 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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t-k]) \tabularnewline
-16 & -0.134748297622974 \tabularnewline
-15 & 0.00988659604286463 \tabularnewline
-14 & 0.0245254841084851 \tabularnewline
-13 & -0.0262368561627115 \tabularnewline
-12 & 0.401784790241174 \tabularnewline
-11 & 0.131636135333294 \tabularnewline
-10 & -0.118406472823555 \tabularnewline
-9 & 0.18104429618926 \tabularnewline
-8 & 0.0458566978802136 \tabularnewline
-7 & 0.0504585721979536 \tabularnewline
-6 & 0.290276400496628 \tabularnewline
-5 & 0.168763695938089 \tabularnewline
-4 & -0.0430434545938679 \tabularnewline
-3 & 0.146462960407287 \tabularnewline
-2 & 0.025040364795946 \tabularnewline
-1 & 0.0788012723171934 \tabularnewline
0 & 0.604664328209351 \tabularnewline
1 & 0.192419199243157 \tabularnewline
2 & -0.0217236949071001 \tabularnewline
3 & 0.208359812754977 \tabularnewline
4 & 0.0399189158914294 \tabularnewline
5 & 0.119749271209492 \tabularnewline
6 & 0.293395647881458 \tabularnewline
7 & 0.0716124042006511 \tabularnewline
8 & -0.0838651402376216 \tabularnewline
9 & 0.0163820823857289 \tabularnewline
10 & -0.204153871452882 \tabularnewline
11 & 0.00988137256266165 \tabularnewline
12 & 0.436910351606634 \tabularnewline
13 & 0.0250457800472754 \tabularnewline
14 & -0.100073335785255 \tabularnewline
15 & 0.0244495962296422 \tabularnewline
16 & -0.0949036323807035 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6020&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]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]0[/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]-0.134748297622974[/C][/ROW]
[ROW][C]-15[/C][C]0.00988659604286463[/C][/ROW]
[ROW][C]-14[/C][C]0.0245254841084851[/C][/ROW]
[ROW][C]-13[/C][C]-0.0262368561627115[/C][/ROW]
[ROW][C]-12[/C][C]0.401784790241174[/C][/ROW]
[ROW][C]-11[/C][C]0.131636135333294[/C][/ROW]
[ROW][C]-10[/C][C]-0.118406472823555[/C][/ROW]
[ROW][C]-9[/C][C]0.18104429618926[/C][/ROW]
[ROW][C]-8[/C][C]0.0458566978802136[/C][/ROW]
[ROW][C]-7[/C][C]0.0504585721979536[/C][/ROW]
[ROW][C]-6[/C][C]0.290276400496628[/C][/ROW]
[ROW][C]-5[/C][C]0.168763695938089[/C][/ROW]
[ROW][C]-4[/C][C]-0.0430434545938679[/C][/ROW]
[ROW][C]-3[/C][C]0.146462960407287[/C][/ROW]
[ROW][C]-2[/C][C]0.025040364795946[/C][/ROW]
[ROW][C]-1[/C][C]0.0788012723171934[/C][/ROW]
[ROW][C]0[/C][C]0.604664328209351[/C][/ROW]
[ROW][C]1[/C][C]0.192419199243157[/C][/ROW]
[ROW][C]2[/C][C]-0.0217236949071001[/C][/ROW]
[ROW][C]3[/C][C]0.208359812754977[/C][/ROW]
[ROW][C]4[/C][C]0.0399189158914294[/C][/ROW]
[ROW][C]5[/C][C]0.119749271209492[/C][/ROW]
[ROW][C]6[/C][C]0.293395647881458[/C][/ROW]
[ROW][C]7[/C][C]0.0716124042006511[/C][/ROW]
[ROW][C]8[/C][C]-0.0838651402376216[/C][/ROW]
[ROW][C]9[/C][C]0.0163820823857289[/C][/ROW]
[ROW][C]10[/C][C]-0.204153871452882[/C][/ROW]
[ROW][C]11[/C][C]0.00988137256266165[/C][/ROW]
[ROW][C]12[/C][C]0.436910351606634[/C][/ROW]
[ROW][C]13[/C][C]0.0250457800472754[/C][/ROW]
[ROW][C]14[/C][C]-0.100073335785255[/C][/ROW]
[ROW][C]15[/C][C]0.0244495962296422[/C][/ROW]
[ROW][C]16[/C][C]-0.0949036323807035[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6020&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6020&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 series0
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 series0
krho(Y[t],X[t-k])
-16-0.134748297622974
-150.00988659604286463
-140.0245254841084851
-13-0.0262368561627115
-120.401784790241174
-110.131636135333294
-10-0.118406472823555
-90.18104429618926
-80.0458566978802136
-70.0504585721979536
-60.290276400496628
-50.168763695938089
-4-0.0430434545938679
-30.146462960407287
-20.025040364795946
-10.0788012723171934
00.604664328209351
10.192419199243157
2-0.0217236949071001
30.208359812754977
40.0399189158914294
50.119749271209492
60.293395647881458
70.0716124042006511
8-0.0838651402376216
90.0163820823857289
10-0.204153871452882
110.00988137256266165
120.436910351606634
130.0250457800472754
14-0.100073335785255
150.0244495962296422
16-0.0949036323807035


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; 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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')