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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, 11 Dec 2007 03:52:09 -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/11/t1197369475kyyz8cx9sy9j9cv.htm/, Retrieved Sun, 28 Apr 2024 22:47:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3098, Retrieved Sun, 28 Apr 2024 22:47:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact223

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...] [2007-12-11 10:52:09] [7c5c775a3769ba2649d285a4261e023c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
467 037
460 070
447 988
442 867
436 087
431 328
484 015
509 673
512 927
502 831
470 984
471 067
476 049
474 605
470 439
461 251
454 724
455 626
516 847
525 192
522 975
518 585
509 239
512 238
519 164
517 009
509 933
509 127
500 857
506 971
569 323
579 714
577 992
565 464
547 344
554 788
562 325
560 854
555 332
543 599
536 662
542 722
593 530
610 763
612 613
611 324
594 167
595 454
590 865
589 379
584 428
573 100
567 456
569 028
620 735
628 884
628 232
612 117
595 404
597 141
593 408
590 072
579 799
574 205
572 775
572 942
619 567
625 809
619 916
587 625
565 742
557 274
Dataseries Y:
Download CSV
Histogram 
90.8
96.4
90
92.1
97.2
95.1
88.5
91
90.5
75
66.3
66
68.4
70.6
83.9
90.1
90.6
87.1
90.8
94.1
99.8
96.8
87
96.3
107.1
115.2
106.1
89.5
91.3
97.6
100.7
104.6
94.7
101.8
102.5
105.3
110.3
109.8
117.3
118.8
131.3
125.9
133.1
147
145.8
164.4
149.8
137.7
151.7
156.8
180
180.4
170.4
191.6
199.5
218.2
217.5
205
194
199.3
219.3
211.1
215.2
240.2
242.2
240.7
255.4
253
218.2
203.7
205.6
215.6

Tables (Output of Computation)





Summary of compuational 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 compuational 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=3098&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]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=3098&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3098&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 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 series1
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 series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-15-0.152099735918114
-14-0.29697839025558
-130.105625632407505
-120.195047580568078
-110.0759511677242402
-100.012705002728991
-9-0.0600459288190955
-80.119703779117033
-70.127043798639659
-60.222332629607161
-50.0203051840271374
-4-0.258572436689882
-3-0.242632827967569
-2-0.304143499621294
-10.122563851771001
00.226468888103857
10.158475224403128
20.0316532317288248
3-0.0549757974096172
40.0748990018530077
50.0505275053604667
60.142311663782541
7-0.0344985179715576
8-0.267641545712153
9-0.201074243774083
10-0.105044653994711
110.178078093109904
120.116070828226675
130.0337430880704969
14-0.0558885729230226
15-0.146343321206918

\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 & 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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & -0.152099735918114 \tabularnewline
-14 & -0.29697839025558 \tabularnewline
-13 & 0.105625632407505 \tabularnewline
-12 & 0.195047580568078 \tabularnewline
-11 & 0.0759511677242402 \tabularnewline
-10 & 0.012705002728991 \tabularnewline
-9 & -0.0600459288190955 \tabularnewline
-8 & 0.119703779117033 \tabularnewline
-7 & 0.127043798639659 \tabularnewline
-6 & 0.222332629607161 \tabularnewline
-5 & 0.0203051840271374 \tabularnewline
-4 & -0.258572436689882 \tabularnewline
-3 & -0.242632827967569 \tabularnewline
-2 & -0.304143499621294 \tabularnewline
-1 & 0.122563851771001 \tabularnewline
0 & 0.226468888103857 \tabularnewline
1 & 0.158475224403128 \tabularnewline
2 & 0.0316532317288248 \tabularnewline
3 & -0.0549757974096172 \tabularnewline
4 & 0.0748990018530077 \tabularnewline
5 & 0.0505275053604667 \tabularnewline
6 & 0.142311663782541 \tabularnewline
7 & -0.0344985179715576 \tabularnewline
8 & -0.267641545712153 \tabularnewline
9 & -0.201074243774083 \tabularnewline
10 & -0.105044653994711 \tabularnewline
11 & 0.178078093109904 \tabularnewline
12 & 0.116070828226675 \tabularnewline
13 & 0.0337430880704969 \tabularnewline
14 & -0.0558885729230226 \tabularnewline
15 & -0.146343321206918 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3098&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]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]1[/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]-15[/C][C]-0.152099735918114[/C][/ROW]
[ROW][C]-14[/C][C]-0.29697839025558[/C][/ROW]
[ROW][C]-13[/C][C]0.105625632407505[/C][/ROW]
[ROW][C]-12[/C][C]0.195047580568078[/C][/ROW]
[ROW][C]-11[/C][C]0.0759511677242402[/C][/ROW]
[ROW][C]-10[/C][C]0.012705002728991[/C][/ROW]
[ROW][C]-9[/C][C]-0.0600459288190955[/C][/ROW]
[ROW][C]-8[/C][C]0.119703779117033[/C][/ROW]
[ROW][C]-7[/C][C]0.127043798639659[/C][/ROW]
[ROW][C]-6[/C][C]0.222332629607161[/C][/ROW]
[ROW][C]-5[/C][C]0.0203051840271374[/C][/ROW]
[ROW][C]-4[/C][C]-0.258572436689882[/C][/ROW]
[ROW][C]-3[/C][C]-0.242632827967569[/C][/ROW]
[ROW][C]-2[/C][C]-0.304143499621294[/C][/ROW]
[ROW][C]-1[/C][C]0.122563851771001[/C][/ROW]
[ROW][C]0[/C][C]0.226468888103857[/C][/ROW]
[ROW][C]1[/C][C]0.158475224403128[/C][/ROW]
[ROW][C]2[/C][C]0.0316532317288248[/C][/ROW]
[ROW][C]3[/C][C]-0.0549757974096172[/C][/ROW]
[ROW][C]4[/C][C]0.0748990018530077[/C][/ROW]
[ROW][C]5[/C][C]0.0505275053604667[/C][/ROW]
[ROW][C]6[/C][C]0.142311663782541[/C][/ROW]
[ROW][C]7[/C][C]-0.0344985179715576[/C][/ROW]
[ROW][C]8[/C][C]-0.267641545712153[/C][/ROW]
[ROW][C]9[/C][C]-0.201074243774083[/C][/ROW]
[ROW][C]10[/C][C]-0.105044653994711[/C][/ROW]
[ROW][C]11[/C][C]0.178078093109904[/C][/ROW]
[ROW][C]12[/C][C]0.116070828226675[/C][/ROW]
[ROW][C]13[/C][C]0.0337430880704969[/C][/ROW]
[ROW][C]14[/C][C]-0.0558885729230226[/C][/ROW]
[ROW][C]15[/C][C]-0.146343321206918[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3098&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3098&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 series0
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 series0
krho(Y[t],X[t+k])
-15-0.152099735918114
-14-0.29697839025558
-130.105625632407505
-120.195047580568078
-110.0759511677242402
-100.012705002728991
-9-0.0600459288190955
-80.119703779117033
-70.127043798639659
-60.222332629607161
-50.0203051840271374
-4-0.258572436689882
-3-0.242632827967569
-2-0.304143499621294
-10.122563851771001
00.226468888103857
10.158475224403128
20.0316532317288248
3-0.0549757974096172
40.0748990018530077
50.0505275053604667
60.142311663782541
7-0.0344985179715576
8-0.267641545712153
9-0.201074243774083
10-0.105044653994711
110.178078093109904
120.116070828226675
130.0337430880704969
14-0.0558885729230226
15-0.146343321206918


Figures (Output of Computation)

Input Parameters & R Code

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