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of Irreproducible Research!

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationWed, 03 Dec 2008 00:55:57 -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/t1228291003g5p7ua5f0p4qb5h.htm/, Retrieved Sun, 19 May 2024 06:28:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28560, Retrieved Sun, 19 May 2024 06:28:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSeverijns Britt
Estimated Impact227
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Cross Correlation Function] [non stationary ti...] [2008-12-03 07:55:57] [7bf28d4d60530086dbc44ae6b648927e] [Current]
Feedback Forum
2008-12-08 18:12:04 [Jessica Alves Pires] [reply
Er is enkel een link opgegeven, er is geen uitleg bij gegeven.
2008-12-08 20:00:49 [Vincent Dolhain] [reply
je had kunnen vermelden dat de autocorrelatie is weg gewerkt. De externe ivloed is ds weg

Post a new message
Dataseries X:
98,1
101,1
111,1
93,3
100
108
70,4
75,4
105,5
112,3
102,5
93,5
86,7
95,2
103,8
97
95,5
101
67,5
64
106,7
100,6
101,2
93,1
84,2
85,8
91,8
92,4
80,3
79,7
62,5
57,1
100,8
100,7
86,2
83,2
71,7
77,5
89,8
80,3
78,7
93,8
57,6
60,6
91
85,3
77,4
77,3
68,3
69,9
81,7
75,1
69,9
84
54,3
60
89,9
77
85,3
77,6
69,2
75,5
85,7
72,2
79,9
85,3
52,2
61,2
82,4
85,4
78,2
70,2
70,2
69,3
77,5
66,1
69
79,2
56,2
63,3
77,8
92
78,1
65,1
71,1
70,9
72
81,9
70,6
72,5
65,1
54,9
Dataseries Y:
467037
460070
447988
442867
436087
431328
484015
509673
512927
502831
470984
471067
476049
474605
470439
461251
454724
455626
516847
525192
522975
518585
509239
512238
519164
517009
509933
509127
500857
506971
569323
579714
577992
565464
547344
554788
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
533590




Summary of computational 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 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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28560&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28560&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28560&T=0

As an alternative you can also use a 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'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 series1
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 series1
krho(Y[t],X[t+k])
-15-0.0464359615852196
-140.164074345080775
-13-0.0644846706579385
-120.041200124427479
-11-0.0495751141887925
-10-0.0106953407670043
-90.0288217487356010
-80.038955751397577
-7-0.0672611586491429
-60.0235276525913468
-50.0997815858523564
-4-0.0196114523965372
-30.0846154092927118
-20.0424831692682096
-1-0.245785919442603
00.199544813034206
1-0.0602548117109802
2-0.0506110352967698
30.0413047735165482
4-0.0671409192518865
5-0.00392965643589621
60.163706353991856
7-0.325451254679981
80.0467536040466612
90.220489730627043
10-0.198001777335512
110.0473169067053938
12-0.045297345047715
130.0144602621105448
14-0.0126640449859286
150.137941667779640

\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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & -0.0464359615852196 \tabularnewline
-14 & 0.164074345080775 \tabularnewline
-13 & -0.0644846706579385 \tabularnewline
-12 & 0.041200124427479 \tabularnewline
-11 & -0.0495751141887925 \tabularnewline
-10 & -0.0106953407670043 \tabularnewline
-9 & 0.0288217487356010 \tabularnewline
-8 & 0.038955751397577 \tabularnewline
-7 & -0.0672611586491429 \tabularnewline
-6 & 0.0235276525913468 \tabularnewline
-5 & 0.0997815858523564 \tabularnewline
-4 & -0.0196114523965372 \tabularnewline
-3 & 0.0846154092927118 \tabularnewline
-2 & 0.0424831692682096 \tabularnewline
-1 & -0.245785919442603 \tabularnewline
0 & 0.199544813034206 \tabularnewline
1 & -0.0602548117109802 \tabularnewline
2 & -0.0506110352967698 \tabularnewline
3 & 0.0413047735165482 \tabularnewline
4 & -0.0671409192518865 \tabularnewline
5 & -0.00392965643589621 \tabularnewline
6 & 0.163706353991856 \tabularnewline
7 & -0.325451254679981 \tabularnewline
8 & 0.0467536040466612 \tabularnewline
9 & 0.220489730627043 \tabularnewline
10 & -0.198001777335512 \tabularnewline
11 & 0.0473169067053938 \tabularnewline
12 & -0.045297345047715 \tabularnewline
13 & 0.0144602621105448 \tabularnewline
14 & -0.0126640449859286 \tabularnewline
15 & 0.137941667779640 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28560&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]1[/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]-0.0464359615852196[/C][/ROW]
[ROW][C]-14[/C][C]0.164074345080775[/C][/ROW]
[ROW][C]-13[/C][C]-0.0644846706579385[/C][/ROW]
[ROW][C]-12[/C][C]0.041200124427479[/C][/ROW]
[ROW][C]-11[/C][C]-0.0495751141887925[/C][/ROW]
[ROW][C]-10[/C][C]-0.0106953407670043[/C][/ROW]
[ROW][C]-9[/C][C]0.0288217487356010[/C][/ROW]
[ROW][C]-8[/C][C]0.038955751397577[/C][/ROW]
[ROW][C]-7[/C][C]-0.0672611586491429[/C][/ROW]
[ROW][C]-6[/C][C]0.0235276525913468[/C][/ROW]
[ROW][C]-5[/C][C]0.0997815858523564[/C][/ROW]
[ROW][C]-4[/C][C]-0.0196114523965372[/C][/ROW]
[ROW][C]-3[/C][C]0.0846154092927118[/C][/ROW]
[ROW][C]-2[/C][C]0.0424831692682096[/C][/ROW]
[ROW][C]-1[/C][C]-0.245785919442603[/C][/ROW]
[ROW][C]0[/C][C]0.199544813034206[/C][/ROW]
[ROW][C]1[/C][C]-0.0602548117109802[/C][/ROW]
[ROW][C]2[/C][C]-0.0506110352967698[/C][/ROW]
[ROW][C]3[/C][C]0.0413047735165482[/C][/ROW]
[ROW][C]4[/C][C]-0.0671409192518865[/C][/ROW]
[ROW][C]5[/C][C]-0.00392965643589621[/C][/ROW]
[ROW][C]6[/C][C]0.163706353991856[/C][/ROW]
[ROW][C]7[/C][C]-0.325451254679981[/C][/ROW]
[ROW][C]8[/C][C]0.0467536040466612[/C][/ROW]
[ROW][C]9[/C][C]0.220489730627043[/C][/ROW]
[ROW][C]10[/C][C]-0.198001777335512[/C][/ROW]
[ROW][C]11[/C][C]0.0473169067053938[/C][/ROW]
[ROW][C]12[/C][C]-0.045297345047715[/C][/ROW]
[ROW][C]13[/C][C]0.0144602621105448[/C][/ROW]
[ROW][C]14[/C][C]-0.0126640449859286[/C][/ROW]
[ROW][C]15[/C][C]0.137941667779640[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28560&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28560&T=1

As an alternative you can also use a 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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-15-0.0464359615852196
-140.164074345080775
-13-0.0644846706579385
-120.041200124427479
-11-0.0495751141887925
-10-0.0106953407670043
-90.0288217487356010
-80.038955751397577
-7-0.0672611586491429
-60.0235276525913468
-50.0997815858523564
-4-0.0196114523965372
-30.0846154092927118
-20.0424831692682096
-1-0.245785919442603
00.199544813034206
1-0.0602548117109802
2-0.0506110352967698
30.0413047735165482
4-0.0671409192518865
5-0.00392965643589621
60.163706353991856
7-0.325451254679981
80.0467536040466612
90.220489730627043
10-0.198001777335512
110.0473169067053938
12-0.045297345047715
130.0144602621105448
14-0.0126640449859286
150.137941667779640



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