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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 25 Nov 2007 14:37:43 -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/25/t1196026170eey1c9z69exacq3.htm/, Retrieved Sat, 04 May 2024 07:20:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6560, Retrieved Sat, 04 May 2024 07:20:19 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact195
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [WS9 Cross met] [2007-11-25 21:37:43] [d66dce91cbb8b108f7114f1eb0c2faa2] [Current]
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Dataseries X:
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
Dataseries Y:
2529
2196
3202
2718
2728
2354
2697
2651
2067
2641
2539
2294
2712
2314
3092
2677
2813
2668
2939
2617
2231
2481
2421
2408
2560
2100
3315
2801
2403
3024
2507
2980
2211
2471
2594
2452
2232
2373
3127
2802
2641
2787
2619
2806
2193
2323
2529
2412
2262
2154
3230
2295
2715
2733
2317
2730
1913
2390
2484
1960




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=6560&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=6560&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6560&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 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 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])
-13-0.0371797081634297
-120.234168362953824
-11-0.0519742426975673
-100.0750400439216008
-90.112893616727319
-8-0.0901744907139362
-70.100454320449695
-6-0.0126932933981473
-5-0.109949820870282
-40.0909318897494471
-3-0.0281905201490848
-2-0.0901035304620369
-10.170885385564904
0-0.235439101776265
10.0903754815475004
20.0820103828988126
30.102911738406206
4-0.057664684464976
50.0861310771613565
6-0.157316086383562
70.108251808754815
8-0.0673839606187701
9-0.0324341330311831
10-0.0254783060001931
110.0608263055295866
120.0565930609943535
13-0.111147832134265

\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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.0371797081634297 \tabularnewline
-12 & 0.234168362953824 \tabularnewline
-11 & -0.0519742426975673 \tabularnewline
-10 & 0.0750400439216008 \tabularnewline
-9 & 0.112893616727319 \tabularnewline
-8 & -0.0901744907139362 \tabularnewline
-7 & 0.100454320449695 \tabularnewline
-6 & -0.0126932933981473 \tabularnewline
-5 & -0.109949820870282 \tabularnewline
-4 & 0.0909318897494471 \tabularnewline
-3 & -0.0281905201490848 \tabularnewline
-2 & -0.0901035304620369 \tabularnewline
-1 & 0.170885385564904 \tabularnewline
0 & -0.235439101776265 \tabularnewline
1 & 0.0903754815475004 \tabularnewline
2 & 0.0820103828988126 \tabularnewline
3 & 0.102911738406206 \tabularnewline
4 & -0.057664684464976 \tabularnewline
5 & 0.0861310771613565 \tabularnewline
6 & -0.157316086383562 \tabularnewline
7 & 0.108251808754815 \tabularnewline
8 & -0.0673839606187701 \tabularnewline
9 & -0.0324341330311831 \tabularnewline
10 & -0.0254783060001931 \tabularnewline
11 & 0.0608263055295866 \tabularnewline
12 & 0.0565930609943535 \tabularnewline
13 & -0.111147832134265 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6560&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]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]-13[/C][C]-0.0371797081634297[/C][/ROW]
[ROW][C]-12[/C][C]0.234168362953824[/C][/ROW]
[ROW][C]-11[/C][C]-0.0519742426975673[/C][/ROW]
[ROW][C]-10[/C][C]0.0750400439216008[/C][/ROW]
[ROW][C]-9[/C][C]0.112893616727319[/C][/ROW]
[ROW][C]-8[/C][C]-0.0901744907139362[/C][/ROW]
[ROW][C]-7[/C][C]0.100454320449695[/C][/ROW]
[ROW][C]-6[/C][C]-0.0126932933981473[/C][/ROW]
[ROW][C]-5[/C][C]-0.109949820870282[/C][/ROW]
[ROW][C]-4[/C][C]0.0909318897494471[/C][/ROW]
[ROW][C]-3[/C][C]-0.0281905201490848[/C][/ROW]
[ROW][C]-2[/C][C]-0.0901035304620369[/C][/ROW]
[ROW][C]-1[/C][C]0.170885385564904[/C][/ROW]
[ROW][C]0[/C][C]-0.235439101776265[/C][/ROW]
[ROW][C]1[/C][C]0.0903754815475004[/C][/ROW]
[ROW][C]2[/C][C]0.0820103828988126[/C][/ROW]
[ROW][C]3[/C][C]0.102911738406206[/C][/ROW]
[ROW][C]4[/C][C]-0.057664684464976[/C][/ROW]
[ROW][C]5[/C][C]0.0861310771613565[/C][/ROW]
[ROW][C]6[/C][C]-0.157316086383562[/C][/ROW]
[ROW][C]7[/C][C]0.108251808754815[/C][/ROW]
[ROW][C]8[/C][C]-0.0673839606187701[/C][/ROW]
[ROW][C]9[/C][C]-0.0324341330311831[/C][/ROW]
[ROW][C]10[/C][C]-0.0254783060001931[/C][/ROW]
[ROW][C]11[/C][C]0.0608263055295866[/C][/ROW]
[ROW][C]12[/C][C]0.0565930609943535[/C][/ROW]
[ROW][C]13[/C][C]-0.111147832134265[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6560&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6560&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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0371797081634297
-120.234168362953824
-11-0.0519742426975673
-100.0750400439216008
-90.112893616727319
-8-0.0901744907139362
-70.100454320449695
-6-0.0126932933981473
-5-0.109949820870282
-40.0909318897494471
-3-0.0281905201490848
-2-0.0901035304620369
-10.170885385564904
0-0.235439101776265
10.0903754815475004
20.0820103828988126
30.102911738406206
4-0.057664684464976
50.0861310771613565
6-0.157316086383562
70.108251808754815
8-0.0673839606187701
9-0.0324341330311831
10-0.0254783060001931
110.0608263055295866
120.0565930609943535
13-0.111147832134265



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