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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 01 Dec 2008 12:38:27 -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/01/t1228160442w7rqhqi4c6kd3ro.htm/, Retrieved Sun, 05 May 2024 16:00:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27252, Retrieved Sun, 05 May 2024 16:00:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Cross Correlation Function] [Cross Corr] [2008-12-01 19:38:27] [21d7d81e7693ad6dde5aadefb1046611] [Current]
F    D    [Cross Correlation Function] [Task 7: Q7] [2008-12-01 20:53:01] [70cb582895831af4be81fec73c607e93]
F   PD    [Cross Correlation Function] [Task 7: Q9] [2008-12-01 20:56:55] [70cb582895831af4be81fec73c607e93]
-    D    [Cross Correlation Function] [Q7] [2008-12-01 21:05:49] [29647dffafb5b58c12a48dbf6cba2b57]
Feedback Forum
2008-12-08 18:29:37 [Jeroen Michel] [reply] 
Hier maak je wel een correcte output, maar ontbreekt enige analyse. Voor deze analyse mag je mij steeds contacteren of indien echt noodzakelijk Prof. Wessa. Probeer zelf eerst een analyse/conclusie te formuleren en nadien kan ik hier in het slechtste geval nog feedback over geven.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
604,4
883,9
527,9
756,2
812,9
655,6
707,6
612,6
659,2
833,4
727,8
797,2
753
762
613,7
759,2
816,4
736,8
680,1
736,5
637,2
801,9
772,3
897,3
792,1
826,8
666,8
906,6
871,4
891
739,2
833,6
715,6
871,6
751,6
1005,5
681,2
837,3
674,7
806,3
860,2
689,8
691,6
682,6
800,1
1023,7
733,5
875,3
770,2
1005,7
982,3
742,9
974,2
822,3
773,2
750,9
708
690
652,8
620,7
461,9
Dataseries Y:
Download CSV
Histogram 
882,5
789,6
773,3
804,3
817,8
836,7
721,8
760,8
841,4
1045,6
949,2
850,1
957,4
851,8
913,9
888
973,8
927,6
833
879,5
797,3
834,5
735,1
835
892,8
697,2
821,1
732,7
797,6
866,3
826,3
778,6
779,2
951
692,3
841,4
857,3
760,7
841,2
810,3
1007,4
931,3
931,2
855,8
858,4
925,9
930,7
1037,6
979,2
942,6
843,9
854,3
1029,8
944
856,4
1059,4
959,3
941,5
1026,4
921,3
968

Tables (Output of Computation)





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=27252&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=27252&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27252&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 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 series0
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)1
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])
-140.0240372407273621
-130.219188662415087
-120.115914854378758
-110.126080472757189
-100.0335550704390506
-9-0.0454366412588724
-80.257445283625162
-70.0992118009826102
-60.142395698911781
-50.143171329476898
-4-0.0457781732394804
-30.0976028714054256
-2-0.0175883664087282
-10.0143756060320425
00.0539851550557108
1-0.105704597761053
2-0.104146177715491
3-0.129196650808231
40.0138480709230249
5-0.0601474559771336
6-0.0562152766817224
70.0193266591147478
8-0.181854598288344
90.00154861115212161
10-0.13821939625075
11-0.0948163317152725
12-0.0141914605302780
13-0.171939182064552
14-0.0266717276739398

\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) & 1 \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 & 0.0240372407273621 \tabularnewline
-13 & 0.219188662415087 \tabularnewline
-12 & 0.115914854378758 \tabularnewline
-11 & 0.126080472757189 \tabularnewline
-10 & 0.0335550704390506 \tabularnewline
-9 & -0.0454366412588724 \tabularnewline
-8 & 0.257445283625162 \tabularnewline
-7 & 0.0992118009826102 \tabularnewline
-6 & 0.142395698911781 \tabularnewline
-5 & 0.143171329476898 \tabularnewline
-4 & -0.0457781732394804 \tabularnewline
-3 & 0.0976028714054256 \tabularnewline
-2 & -0.0175883664087282 \tabularnewline
-1 & 0.0143756060320425 \tabularnewline
0 & 0.0539851550557108 \tabularnewline
1 & -0.105704597761053 \tabularnewline
2 & -0.104146177715491 \tabularnewline
3 & -0.129196650808231 \tabularnewline
4 & 0.0138480709230249 \tabularnewline
5 & -0.0601474559771336 \tabularnewline
6 & -0.0562152766817224 \tabularnewline
7 & 0.0193266591147478 \tabularnewline
8 & -0.181854598288344 \tabularnewline
9 & 0.00154861115212161 \tabularnewline
10 & -0.13821939625075 \tabularnewline
11 & -0.0948163317152725 \tabularnewline
12 & -0.0141914605302780 \tabularnewline
13 & -0.171939182064552 \tabularnewline
14 & -0.0266717276739398 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27252&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]1[/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]0.0240372407273621[/C][/ROW]
[ROW][C]-13[/C][C]0.219188662415087[/C][/ROW]
[ROW][C]-12[/C][C]0.115914854378758[/C][/ROW]
[ROW][C]-11[/C][C]0.126080472757189[/C][/ROW]
[ROW][C]-10[/C][C]0.0335550704390506[/C][/ROW]
[ROW][C]-9[/C][C]-0.0454366412588724[/C][/ROW]
[ROW][C]-8[/C][C]0.257445283625162[/C][/ROW]
[ROW][C]-7[/C][C]0.0992118009826102[/C][/ROW]
[ROW][C]-6[/C][C]0.142395698911781[/C][/ROW]
[ROW][C]-5[/C][C]0.143171329476898[/C][/ROW]
[ROW][C]-4[/C][C]-0.0457781732394804[/C][/ROW]
[ROW][C]-3[/C][C]0.0976028714054256[/C][/ROW]
[ROW][C]-2[/C][C]-0.0175883664087282[/C][/ROW]
[ROW][C]-1[/C][C]0.0143756060320425[/C][/ROW]
[ROW][C]0[/C][C]0.0539851550557108[/C][/ROW]
[ROW][C]1[/C][C]-0.105704597761053[/C][/ROW]
[ROW][C]2[/C][C]-0.104146177715491[/C][/ROW]
[ROW][C]3[/C][C]-0.129196650808231[/C][/ROW]
[ROW][C]4[/C][C]0.0138480709230249[/C][/ROW]
[ROW][C]5[/C][C]-0.0601474559771336[/C][/ROW]
[ROW][C]6[/C][C]-0.0562152766817224[/C][/ROW]
[ROW][C]7[/C][C]0.0193266591147478[/C][/ROW]
[ROW][C]8[/C][C]-0.181854598288344[/C][/ROW]
[ROW][C]9[/C][C]0.00154861115212161[/C][/ROW]
[ROW][C]10[/C][C]-0.13821939625075[/C][/ROW]
[ROW][C]11[/C][C]-0.0948163317152725[/C][/ROW]
[ROW][C]12[/C][C]-0.0141914605302780[/C][/ROW]
[ROW][C]13[/C][C]-0.171939182064552[/C][/ROW]
[ROW][C]14[/C][C]-0.0266717276739398[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27252&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27252&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)1
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])
-140.0240372407273621
-130.219188662415087
-120.115914854378758
-110.126080472757189
-100.0335550704390506
-9-0.0454366412588724
-80.257445283625162
-70.0992118009826102
-60.142395698911781
-50.143171329476898
-4-0.0457781732394804
-30.0976028714054256
-2-0.0175883664087282
-10.0143756060320425
00.0539851550557108
1-0.105704597761053
2-0.104146177715491
3-0.129196650808231
40.0138480709230249
5-0.0601474559771336
6-0.0562152766817224
70.0193266591147478
8-0.181854598288344
90.00154861115212161
10-0.13821939625075
11-0.0948163317152725
12-0.0141914605302780
13-0.171939182064552
14-0.0266717276739398


Figures (Output of Computation)

Input Parameters & R Code

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