FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationWed, 28 Nov 2007 13:05:13 -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/28/t1196279701j0w0ydk8hsh2tmv.htm/, Retrieved Thu, 02 May 2024 01:12:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7265, Retrieved Thu, 02 May 2024 01:12:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171

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...] [2007-11-28 20:05:13] [cb51ec34031fa6f7825ad77351c1efd8] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
40,3
38,4
46,9
56,1
57,4
58,5
66,6
71,8
80,7
78,2
85,0
87,6
88,6
95,0
96,3
83,3
96,9
103,4
99,3
103,8
113,4
111,5
114,2
90,6
90,8
96,4
90,0
92,1
97,2
95,1
88,5
91,0
90,5
75,0
66,3
66,0
68,4
70,6
83,9
90,1
90,6
87,1
90,8
94,1
99,8
96,8
87,0
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
Dataseries Y:
Download CSV
Histogram 
544,5
619,8
777,6
640,4
633,0
722,0
860,1
495,1
692,8
766,7
648,5
640,0
681,6
752,5
1031,7
685,5
887,6
655,4
944,2
626,6
1221,8
939,6
886,6
811,3
774,7
910,6
911,6
697,7
829,8
824,3
885,6
538,9
686,0
878,7
812,7
640,4
773,9
795,9
836,3
876,1
851,7
692,4
877,3
536,8
705,9
951,0
755,7
695,5
744,8
672,1
666,6
760,8
756,0
604,4
883,9
527,9
756,2
812,9
655,6
707,6

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=7265&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=7265&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7265&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 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])
-14-0.180287902701044
-13-0.131878993129685
-12-0.0578514357399949
-11-0.0720173492870805
-100.0104876437371261
-90.0478204427864289
-80.13156475502469
-70.205667499187403
-60.145823694119810
-50.0873626107575822
-40.177491234453361
-30.177131384082490
-20.189799794715713
-10.242357687828097
00.290525215000699
10.220416444696427
20.258320330555037
30.179311008553663
40.155403423451591
50.115556240061601
60.0413347665122204
70.0190972160030159
80.0307122964142452
9-0.0724507794295444
10-0.0812278587267688
11-0.0608529716358435
12-0.131927714447459
13-0.192167471572635
14-0.165395226367884

\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
-14 & -0.180287902701044 \tabularnewline
-13 & -0.131878993129685 \tabularnewline
-12 & -0.0578514357399949 \tabularnewline
-11 & -0.0720173492870805 \tabularnewline
-10 & 0.0104876437371261 \tabularnewline
-9 & 0.0478204427864289 \tabularnewline
-8 & 0.13156475502469 \tabularnewline
-7 & 0.205667499187403 \tabularnewline
-6 & 0.145823694119810 \tabularnewline
-5 & 0.0873626107575822 \tabularnewline
-4 & 0.177491234453361 \tabularnewline
-3 & 0.177131384082490 \tabularnewline
-2 & 0.189799794715713 \tabularnewline
-1 & 0.242357687828097 \tabularnewline
0 & 0.290525215000699 \tabularnewline
1 & 0.220416444696427 \tabularnewline
2 & 0.258320330555037 \tabularnewline
3 & 0.179311008553663 \tabularnewline
4 & 0.155403423451591 \tabularnewline
5 & 0.115556240061601 \tabularnewline
6 & 0.0413347665122204 \tabularnewline
7 & 0.0190972160030159 \tabularnewline
8 & 0.0307122964142452 \tabularnewline
9 & -0.0724507794295444 \tabularnewline
10 & -0.0812278587267688 \tabularnewline
11 & -0.0608529716358435 \tabularnewline
12 & -0.131927714447459 \tabularnewline
13 & -0.192167471572635 \tabularnewline
14 & -0.165395226367884 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7265&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]-14[/C][C]-0.180287902701044[/C][/ROW]
[ROW][C]-13[/C][C]-0.131878993129685[/C][/ROW]
[ROW][C]-12[/C][C]-0.0578514357399949[/C][/ROW]
[ROW][C]-11[/C][C]-0.0720173492870805[/C][/ROW]
[ROW][C]-10[/C][C]0.0104876437371261[/C][/ROW]
[ROW][C]-9[/C][C]0.0478204427864289[/C][/ROW]
[ROW][C]-8[/C][C]0.13156475502469[/C][/ROW]
[ROW][C]-7[/C][C]0.205667499187403[/C][/ROW]
[ROW][C]-6[/C][C]0.145823694119810[/C][/ROW]
[ROW][C]-5[/C][C]0.0873626107575822[/C][/ROW]
[ROW][C]-4[/C][C]0.177491234453361[/C][/ROW]
[ROW][C]-3[/C][C]0.177131384082490[/C][/ROW]
[ROW][C]-2[/C][C]0.189799794715713[/C][/ROW]
[ROW][C]-1[/C][C]0.242357687828097[/C][/ROW]
[ROW][C]0[/C][C]0.290525215000699[/C][/ROW]
[ROW][C]1[/C][C]0.220416444696427[/C][/ROW]
[ROW][C]2[/C][C]0.258320330555037[/C][/ROW]
[ROW][C]3[/C][C]0.179311008553663[/C][/ROW]
[ROW][C]4[/C][C]0.155403423451591[/C][/ROW]
[ROW][C]5[/C][C]0.115556240061601[/C][/ROW]
[ROW][C]6[/C][C]0.0413347665122204[/C][/ROW]
[ROW][C]7[/C][C]0.0190972160030159[/C][/ROW]
[ROW][C]8[/C][C]0.0307122964142452[/C][/ROW]
[ROW][C]9[/C][C]-0.0724507794295444[/C][/ROW]
[ROW][C]10[/C][C]-0.0812278587267688[/C][/ROW]
[ROW][C]11[/C][C]-0.0608529716358435[/C][/ROW]
[ROW][C]12[/C][C]-0.131927714447459[/C][/ROW]
[ROW][C]13[/C][C]-0.192167471572635[/C][/ROW]
[ROW][C]14[/C][C]-0.165395226367884[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7265&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7265&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])
-14-0.180287902701044
-13-0.131878993129685
-12-0.0578514357399949
-11-0.0720173492870805
-100.0104876437371261
-90.0478204427864289
-80.13156475502469
-70.205667499187403
-60.145823694119810
-50.0873626107575822
-40.177491234453361
-30.177131384082490
-20.189799794715713
-10.242357687828097
00.290525215000699
10.220416444696427
20.258320330555037
30.179311008553663
40.155403423451591
50.115556240061601
60.0413347665122204
70.0190972160030159
80.0307122964142452
9-0.0724507794295444
10-0.0812278587267688
11-0.0608529716358435
12-0.131927714447459
13-0.192167471572635
14-0.165395226367884


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')