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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 computationWed, 28 Nov 2007 13:07:35 -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/t11962798373o4e8vkw2t4bemg.htm/, Retrieved Thu, 02 May 2024 09:38:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7266, Retrieved Thu, 02 May 2024 09:38:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact175

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 20:07:35] [cb51ec34031fa6f7825ad77351c1efd8] [Current]
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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 
733,6
844,9
864,3
833,5
814,9
820,4
710,8
773,1
801,2
832,9
808,3
817,2
745,5
932,6
1057,0
879,9
1089,5
903,0
846,1
959,1
952,0
1092,5
1188,9
996,7
1034,3
898,2
1111,6
900,5
1049,2
1010,9
875,9
849,9
713,4
918,6
912,5
767,0
902,2
891,9
874,0
930,9
944,2
935,9
937,1
885,1
892,4
987,3
946,3
799,6
875,4
846,2
880,6
885,7
868,9
882,5
789,6
773,3
804,3
817,8
836,7
721,8

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=7266&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=7266&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7266&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])
-14-0.261423175249815
-13-0.234411644257932
-12-0.130373515831582
-11-0.106748470918852
-10-0.0631143790296958
-90.0410300090623117
-80.140080701880574
-70.162047300030325
-60.266111686860931
-50.276998486697201
-40.306826794543292
-30.332316872237246
-20.361275358928289
-10.342918011635815
00.354732530073943
10.285314009718786
20.240229870747509
30.267290794347297
40.209697414585283
50.151655332786778
60.108097862584555
7-0.0104593370277434
8-0.0582782695857475
9-0.09526774326797
10-0.180138141830387
11-0.197524943308236
12-0.238099837400926
13-0.258914175353065
14-0.237214632194206

\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 & -0.261423175249815 \tabularnewline
-13 & -0.234411644257932 \tabularnewline
-12 & -0.130373515831582 \tabularnewline
-11 & -0.106748470918852 \tabularnewline
-10 & -0.0631143790296958 \tabularnewline
-9 & 0.0410300090623117 \tabularnewline
-8 & 0.140080701880574 \tabularnewline
-7 & 0.162047300030325 \tabularnewline
-6 & 0.266111686860931 \tabularnewline
-5 & 0.276998486697201 \tabularnewline
-4 & 0.306826794543292 \tabularnewline
-3 & 0.332316872237246 \tabularnewline
-2 & 0.361275358928289 \tabularnewline
-1 & 0.342918011635815 \tabularnewline
0 & 0.354732530073943 \tabularnewline
1 & 0.285314009718786 \tabularnewline
2 & 0.240229870747509 \tabularnewline
3 & 0.267290794347297 \tabularnewline
4 & 0.209697414585283 \tabularnewline
5 & 0.151655332786778 \tabularnewline
6 & 0.108097862584555 \tabularnewline
7 & -0.0104593370277434 \tabularnewline
8 & -0.0582782695857475 \tabularnewline
9 & -0.09526774326797 \tabularnewline
10 & -0.180138141830387 \tabularnewline
11 & -0.197524943308236 \tabularnewline
12 & -0.238099837400926 \tabularnewline
13 & -0.258914175353065 \tabularnewline
14 & -0.237214632194206 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7266&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]-0.261423175249815[/C][/ROW]
[ROW][C]-13[/C][C]-0.234411644257932[/C][/ROW]
[ROW][C]-12[/C][C]-0.130373515831582[/C][/ROW]
[ROW][C]-11[/C][C]-0.106748470918852[/C][/ROW]
[ROW][C]-10[/C][C]-0.0631143790296958[/C][/ROW]
[ROW][C]-9[/C][C]0.0410300090623117[/C][/ROW]
[ROW][C]-8[/C][C]0.140080701880574[/C][/ROW]
[ROW][C]-7[/C][C]0.162047300030325[/C][/ROW]
[ROW][C]-6[/C][C]0.266111686860931[/C][/ROW]
[ROW][C]-5[/C][C]0.276998486697201[/C][/ROW]
[ROW][C]-4[/C][C]0.306826794543292[/C][/ROW]
[ROW][C]-3[/C][C]0.332316872237246[/C][/ROW]
[ROW][C]-2[/C][C]0.361275358928289[/C][/ROW]
[ROW][C]-1[/C][C]0.342918011635815[/C][/ROW]
[ROW][C]0[/C][C]0.354732530073943[/C][/ROW]
[ROW][C]1[/C][C]0.285314009718786[/C][/ROW]
[ROW][C]2[/C][C]0.240229870747509[/C][/ROW]
[ROW][C]3[/C][C]0.267290794347297[/C][/ROW]
[ROW][C]4[/C][C]0.209697414585283[/C][/ROW]
[ROW][C]5[/C][C]0.151655332786778[/C][/ROW]
[ROW][C]6[/C][C]0.108097862584555[/C][/ROW]
[ROW][C]7[/C][C]-0.0104593370277434[/C][/ROW]
[ROW][C]8[/C][C]-0.0582782695857475[/C][/ROW]
[ROW][C]9[/C][C]-0.09526774326797[/C][/ROW]
[ROW][C]10[/C][C]-0.180138141830387[/C][/ROW]
[ROW][C]11[/C][C]-0.197524943308236[/C][/ROW]
[ROW][C]12[/C][C]-0.238099837400926[/C][/ROW]
[ROW][C]13[/C][C]-0.258914175353065[/C][/ROW]
[ROW][C]14[/C][C]-0.237214632194206[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7266&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7266&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])
-14-0.261423175249815
-13-0.234411644257932
-12-0.130373515831582
-11-0.106748470918852
-10-0.0631143790296958
-90.0410300090623117
-80.140080701880574
-70.162047300030325
-60.266111686860931
-50.276998486697201
-40.306826794543292
-30.332316872237246
-20.361275358928289
-10.342918011635815
00.354732530073943
10.285314009718786
20.240229870747509
30.267290794347297
40.209697414585283
50.151655332786778
60.108097862584555
7-0.0104593370277434
8-0.0582782695857475
9-0.09526774326797
10-0.180138141830387
11-0.197524943308236
12-0.238099837400926
13-0.258914175353065
14-0.237214632194206


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')