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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, 13 Dec 2007 07:04:53 -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/13/t1197553807ny99y9tukbhox9r.htm/, Retrieved Sun, 05 May 2024 15:42:55 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3542, Retrieved Sun, 05 May 2024 15:42:55 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsbridome
Estimated Impact198

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...] [2007-12-13 14:04:53] [05eb25e9a99d8c3f4eb6a6fe65650e56] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
-1
-4
0
-1
-6
9
-5
1
0
5
0
5
-2
-4
6
5
7
0
8
-2
4
-7
23
6
-11
4
-2
6
7
-4
1
6
8
-18
-5
6
22
3
2
-1
-2
8
-2
5
1
3
0
-9
-8
5
0
1
1
-10
1
0
-11
6
4
11
1
-7
-11
-1
1
0
1
-4
1
-9
-3
-14
0
1
0
-1
-5
5
5
-2
-5
-2
-5
-16
-5
-11
8
-9
-7
0
-14
-12
9
Dataseries Y:
Download CSV
Histogram 
-175
353
78
-17
1506
-1142
282
793
-891
624
-447
-49
-325
707
-565
319
245
-483
118
-348
58
454
-605
127
-382
-154
445
108
907
-555
-115
-674
447
-220
-72
549
-1030
103
-71
1085
-562
559
-500
334
376
-403
156
-470
-309
443
-122
-167
716
262
-665
646
-349
-85
238
-209
-497
1164
407
-906
1342
-1313
67
1556
-1638
-163
379
496
-638
311
-165
287
790
-290
825
-163
-1429
785
261
-454
-267
1232
0
-725
1038
-1135
442
232
-936
98
271
318
-1154
465
130
-511
744
-735
-177
1000
-848

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=3542&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=3542&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3542&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 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])
-160.0593470433452733
-15-0.0471151652425798
-14-0.180651375861471
-130.0248960834441578
-120.175159455955076
-11-0.138220073625992
-100.0765547109021554
-9-0.0287277402382181
-8-0.0418172152341134
-70.109862498956999
-6-0.069164553872464
-5-0.0984434843120394
-40.0882557376895627
-30.0445908500282303
-2-0.0608338397299852
-10.063647304324084
0-0.163553704896819
10.0413077905656635
20.100811578494804
3-0.0507306812345095
40.0738216559734145
5-0.116374269670350
6-0.0730046878989719
70.0152512862603224
80.0584032403742756
9-0.122326075081006
10-0.0128804050535982
110.192714738165975
12-0.191099506357998
130.00342530554787410
14-0.0445806926161109
150.0580833333350537
160.117667371623628

\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 & 0.0593470433452733 \tabularnewline
-15 & -0.0471151652425798 \tabularnewline
-14 & -0.180651375861471 \tabularnewline
-13 & 0.0248960834441578 \tabularnewline
-12 & 0.175159455955076 \tabularnewline
-11 & -0.138220073625992 \tabularnewline
-10 & 0.0765547109021554 \tabularnewline
-9 & -0.0287277402382181 \tabularnewline
-8 & -0.0418172152341134 \tabularnewline
-7 & 0.109862498956999 \tabularnewline
-6 & -0.069164553872464 \tabularnewline
-5 & -0.0984434843120394 \tabularnewline
-4 & 0.0882557376895627 \tabularnewline
-3 & 0.0445908500282303 \tabularnewline
-2 & -0.0608338397299852 \tabularnewline
-1 & 0.063647304324084 \tabularnewline
0 & -0.163553704896819 \tabularnewline
1 & 0.0413077905656635 \tabularnewline
2 & 0.100811578494804 \tabularnewline
3 & -0.0507306812345095 \tabularnewline
4 & 0.0738216559734145 \tabularnewline
5 & -0.116374269670350 \tabularnewline
6 & -0.0730046878989719 \tabularnewline
7 & 0.0152512862603224 \tabularnewline
8 & 0.0584032403742756 \tabularnewline
9 & -0.122326075081006 \tabularnewline
10 & -0.0128804050535982 \tabularnewline
11 & 0.192714738165975 \tabularnewline
12 & -0.191099506357998 \tabularnewline
13 & 0.00342530554787410 \tabularnewline
14 & -0.0445806926161109 \tabularnewline
15 & 0.0580833333350537 \tabularnewline
16 & 0.117667371623628 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3542&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]0.0593470433452733[/C][/ROW]
[ROW][C]-15[/C][C]-0.0471151652425798[/C][/ROW]
[ROW][C]-14[/C][C]-0.180651375861471[/C][/ROW]
[ROW][C]-13[/C][C]0.0248960834441578[/C][/ROW]
[ROW][C]-12[/C][C]0.175159455955076[/C][/ROW]
[ROW][C]-11[/C][C]-0.138220073625992[/C][/ROW]
[ROW][C]-10[/C][C]0.0765547109021554[/C][/ROW]
[ROW][C]-9[/C][C]-0.0287277402382181[/C][/ROW]
[ROW][C]-8[/C][C]-0.0418172152341134[/C][/ROW]
[ROW][C]-7[/C][C]0.109862498956999[/C][/ROW]
[ROW][C]-6[/C][C]-0.069164553872464[/C][/ROW]
[ROW][C]-5[/C][C]-0.0984434843120394[/C][/ROW]
[ROW][C]-4[/C][C]0.0882557376895627[/C][/ROW]
[ROW][C]-3[/C][C]0.0445908500282303[/C][/ROW]
[ROW][C]-2[/C][C]-0.0608338397299852[/C][/ROW]
[ROW][C]-1[/C][C]0.063647304324084[/C][/ROW]
[ROW][C]0[/C][C]-0.163553704896819[/C][/ROW]
[ROW][C]1[/C][C]0.0413077905656635[/C][/ROW]
[ROW][C]2[/C][C]0.100811578494804[/C][/ROW]
[ROW][C]3[/C][C]-0.0507306812345095[/C][/ROW]
[ROW][C]4[/C][C]0.0738216559734145[/C][/ROW]
[ROW][C]5[/C][C]-0.116374269670350[/C][/ROW]
[ROW][C]6[/C][C]-0.0730046878989719[/C][/ROW]
[ROW][C]7[/C][C]0.0152512862603224[/C][/ROW]
[ROW][C]8[/C][C]0.0584032403742756[/C][/ROW]
[ROW][C]9[/C][C]-0.122326075081006[/C][/ROW]
[ROW][C]10[/C][C]-0.0128804050535982[/C][/ROW]
[ROW][C]11[/C][C]0.192714738165975[/C][/ROW]
[ROW][C]12[/C][C]-0.191099506357998[/C][/ROW]
[ROW][C]13[/C][C]0.00342530554787410[/C][/ROW]
[ROW][C]14[/C][C]-0.0445806926161109[/C][/ROW]
[ROW][C]15[/C][C]0.0580833333350537[/C][/ROW]
[ROW][C]16[/C][C]0.117667371623628[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3542&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3542&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])
-160.0593470433452733
-15-0.0471151652425798
-14-0.180651375861471
-130.0248960834441578
-120.175159455955076
-11-0.138220073625992
-100.0765547109021554
-9-0.0287277402382181
-8-0.0418172152341134
-70.109862498956999
-6-0.069164553872464
-5-0.0984434843120394
-40.0882557376895627
-30.0445908500282303
-2-0.0608338397299852
-10.063647304324084
0-0.163553704896819
10.0413077905656635
20.100811578494804
3-0.0507306812345095
40.0738216559734145
5-0.116374269670350
6-0.0730046878989719
70.0152512862603224
80.0584032403742756
9-0.122326075081006
10-0.0128804050535982
110.192714738165975
12-0.191099506357998
130.00342530554787410
14-0.0445806926161109
150.0580833333350537
160.117667371623628


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',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')