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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 computationSun, 06 Jan 2008 14:36:06 -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/Jan/06/t119965532036v53uygptiacvj.htm/, Retrieved Sun, 05 May 2024 07:07:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7912, Retrieved Sun, 05 May 2024 07:07:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInducing time series Q5 EA-TI
Estimated Impact183

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [WS2 - Robustness ...] [2007-10-20 13:06:37] [5343e105a400b9e32bf6f011133bbaf4]
- RM D    [Cross Correlation Function] [CVWS7Q5EA-TI] [2008-01-06 21:36:06] [b523c8d839cc24a05ea912c062a47207] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
13,5
16,2
17,6
15,8
17,6
15,2
15,9
12,0
13,3
14,8
16,1
16,9
17,6
13,9
10,0
7,6
7,1
8,1
8,1
7,7
4,0
1,4
0,3
-1,0
-1,9
-1,5
-0,2
3,4
3,0
4,1
3,4
3,2
6,1
5,8
6,2
5,8
5,9
6,7
5,9
3,8
1,7
1,4
1,8
3,0
3,6
4,8
4,3
4,2
2,9
4,9
7,2
8,7
9,1
8,9
9,0
11,6
9,6
9,1
9,2
10,8
11,0
8,5
6,5
7,2
7,8
8,7
7,8
7,5
7,7
7,5
8,3
7,9
10,4
11,5
14,0
11,9
11,9
10,3
11,3
9,9
8,9
9,2
8,8
6,7
7,1
6,6
7,2
5,0
5,3
6,3
Dataseries Y:
Download CSV
Histogram 
-12.7
-2.4
7.1
-3.9
9.5
5
-16.1
-10.8
7
13.6
8.1
-8.1
4.9
-0.8
4.3
4
1.5
5.4
-11.3
-16.4
-2
8.9
-7.2
-18
1.3
6.3
-6
2.8
2
5.1
-7.6
-18.6
5.8
20.3
0.7
-11.2
-5.7
-0.1
3.4
3.3
-1.2
4.2
-8.8
-25.3
8.5
14.5
-3.1
-10.4
-2.9
0.3
22.6
15.4
9
29.1
2.8
-3.8
27.7
28.9
26.5
19.8
13.2
14.1
34.1
30
21.8
32.1
5.3
3
17.1
26.3
38.1
19.5
38
35.5
78.6
62.2
76.9
104.9
32.2
42.5
64.3
74.9
75.4
43
58.7
55.4
76.6
63.3
78.9
82.7

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=7912&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=7912&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7912&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])
-160.00852732753298934
-150.037823498806461
-140.0477878339312526
-130.0598523137772203
-120.076626722283177
-110.0780969784908756
-100.0957101680039332
-90.108613428857002
-80.140551384923364
-70.157021873987899
-60.149447632647373
-50.149911329971096
-40.165314588581638
-30.183740962359526
-20.174790999573004
-10.161717488308542
00.154592185058199
10.150282128920523
20.162298557785088
30.138910869327569
40.140743587973201
50.128935213484654
60.100154218522412
70.102727390427702
80.100939894226022
90.108450961466687
100.107583834656534
110.101071650780268
120.107223026559414
130.130063803430689
140.159002812024531
150.175906770348225
160.190676720978000

\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
-16 & 0.00852732753298934 \tabularnewline
-15 & 0.037823498806461 \tabularnewline
-14 & 0.0477878339312526 \tabularnewline
-13 & 0.0598523137772203 \tabularnewline
-12 & 0.076626722283177 \tabularnewline
-11 & 0.0780969784908756 \tabularnewline
-10 & 0.0957101680039332 \tabularnewline
-9 & 0.108613428857002 \tabularnewline
-8 & 0.140551384923364 \tabularnewline
-7 & 0.157021873987899 \tabularnewline
-6 & 0.149447632647373 \tabularnewline
-5 & 0.149911329971096 \tabularnewline
-4 & 0.165314588581638 \tabularnewline
-3 & 0.183740962359526 \tabularnewline
-2 & 0.174790999573004 \tabularnewline
-1 & 0.161717488308542 \tabularnewline
0 & 0.154592185058199 \tabularnewline
1 & 0.150282128920523 \tabularnewline
2 & 0.162298557785088 \tabularnewline
3 & 0.138910869327569 \tabularnewline
4 & 0.140743587973201 \tabularnewline
5 & 0.128935213484654 \tabularnewline
6 & 0.100154218522412 \tabularnewline
7 & 0.102727390427702 \tabularnewline
8 & 0.100939894226022 \tabularnewline
9 & 0.108450961466687 \tabularnewline
10 & 0.107583834656534 \tabularnewline
11 & 0.101071650780268 \tabularnewline
12 & 0.107223026559414 \tabularnewline
13 & 0.130063803430689 \tabularnewline
14 & 0.159002812024531 \tabularnewline
15 & 0.175906770348225 \tabularnewline
16 & 0.190676720978000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7912&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]-16[/C][C]0.00852732753298934[/C][/ROW]
[ROW][C]-15[/C][C]0.037823498806461[/C][/ROW]
[ROW][C]-14[/C][C]0.0477878339312526[/C][/ROW]
[ROW][C]-13[/C][C]0.0598523137772203[/C][/ROW]
[ROW][C]-12[/C][C]0.076626722283177[/C][/ROW]
[ROW][C]-11[/C][C]0.0780969784908756[/C][/ROW]
[ROW][C]-10[/C][C]0.0957101680039332[/C][/ROW]
[ROW][C]-9[/C][C]0.108613428857002[/C][/ROW]
[ROW][C]-8[/C][C]0.140551384923364[/C][/ROW]
[ROW][C]-7[/C][C]0.157021873987899[/C][/ROW]
[ROW][C]-6[/C][C]0.149447632647373[/C][/ROW]
[ROW][C]-5[/C][C]0.149911329971096[/C][/ROW]
[ROW][C]-4[/C][C]0.165314588581638[/C][/ROW]
[ROW][C]-3[/C][C]0.183740962359526[/C][/ROW]
[ROW][C]-2[/C][C]0.174790999573004[/C][/ROW]
[ROW][C]-1[/C][C]0.161717488308542[/C][/ROW]
[ROW][C]0[/C][C]0.154592185058199[/C][/ROW]
[ROW][C]1[/C][C]0.150282128920523[/C][/ROW]
[ROW][C]2[/C][C]0.162298557785088[/C][/ROW]
[ROW][C]3[/C][C]0.138910869327569[/C][/ROW]
[ROW][C]4[/C][C]0.140743587973201[/C][/ROW]
[ROW][C]5[/C][C]0.128935213484654[/C][/ROW]
[ROW][C]6[/C][C]0.100154218522412[/C][/ROW]
[ROW][C]7[/C][C]0.102727390427702[/C][/ROW]
[ROW][C]8[/C][C]0.100939894226022[/C][/ROW]
[ROW][C]9[/C][C]0.108450961466687[/C][/ROW]
[ROW][C]10[/C][C]0.107583834656534[/C][/ROW]
[ROW][C]11[/C][C]0.101071650780268[/C][/ROW]
[ROW][C]12[/C][C]0.107223026559414[/C][/ROW]
[ROW][C]13[/C][C]0.130063803430689[/C][/ROW]
[ROW][C]14[/C][C]0.159002812024531[/C][/ROW]
[ROW][C]15[/C][C]0.175906770348225[/C][/ROW]
[ROW][C]16[/C][C]0.190676720978000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7912&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7912&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])
-160.00852732753298934
-150.037823498806461
-140.0477878339312526
-130.0598523137772203
-120.076626722283177
-110.0780969784908756
-100.0957101680039332
-90.108613428857002
-80.140551384923364
-70.157021873987899
-60.149447632647373
-50.149911329971096
-40.165314588581638
-30.183740962359526
-20.174790999573004
-10.161717488308542
00.154592185058199
10.150282128920523
20.162298557785088
30.138910869327569
40.140743587973201
50.128935213484654
60.100154218522412
70.102727390427702
80.100939894226022
90.108450961466687
100.107583834656534
110.101071650780268
120.107223026559414
130.130063803430689
140.159002812024531
150.175906770348225
160.190676720978000


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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',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')