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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 14:32:54 -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/t1199655124yjzl8elrpbpqtjk.htm/, Retrieved Sun, 05 May 2024 05:26:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7909, Retrieved Sun, 05 May 2024 05:26:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInducing time series Q5 WL-TI
Estimated Impact166

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] [CVWS7Q5WL-TI] [2008-01-06 21:32:54] [b523c8d839cc24a05ea912c062a47207] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
7.3
7.2
7.1
6.9
6.8
6.7
6.8
6.8
6.7
6.8
6.8
6.7
6.3
6.2
6.2
6.5
6.5
6.4
6.2
6.2
6.3
7.5
7.4
7.4
7.4
7.4
7.4
7.2
7.2
7.2
7.5
7.4
7.5
8.0
8.0
8.0
8.1
8.1
8.1
7.9
7.9
8.0
8.2
8.1
8.2
8.5
8.5
8.6
8.4
8.4
8.4
7.7
7.8
7.9
8.8
8.8
8.9
8.5
8.5
8.5
8.4
8.5
8.4
8.3
8.4
8.4
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.5
8.3
8.3
8.3
8.2
8.1
8.1
8.2
8.0
7.9
7.9
7.8
7.7
7.9
7.7
7.6
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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 3 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7909&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]3 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7909&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7909&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 time3 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






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])
-160.646968800104545
-150.646171947072123
-140.613097913532082
-130.590371602041709
-120.58865498374925
-110.58971846602711
-100.561500778545096
-90.553220611816891
-80.55804431800832
-70.535639392143397
-60.514902236321267
-50.483165394384291
-40.482265485065501
-30.469972050114942
-20.418908162867003
-10.378247033596314
00.356723650237328
10.329387830504097
20.283584977427138
30.254143882266375
40.243091560569900
50.222003951551093
60.185118007364811
70.144835923093565
80.129976445747474
90.112434239087552
100.0812196565198096
110.0534264942762935
120.0333791247677876
130.0172798270751182
14-0.0211603075144018
15-0.0530531020512435
16-0.0558156825152876

\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 & 0.646968800104545 \tabularnewline
-15 & 0.646171947072123 \tabularnewline
-14 & 0.613097913532082 \tabularnewline
-13 & 0.590371602041709 \tabularnewline
-12 & 0.58865498374925 \tabularnewline
-11 & 0.58971846602711 \tabularnewline
-10 & 0.561500778545096 \tabularnewline
-9 & 0.553220611816891 \tabularnewline
-8 & 0.55804431800832 \tabularnewline
-7 & 0.535639392143397 \tabularnewline
-6 & 0.514902236321267 \tabularnewline
-5 & 0.483165394384291 \tabularnewline
-4 & 0.482265485065501 \tabularnewline
-3 & 0.469972050114942 \tabularnewline
-2 & 0.418908162867003 \tabularnewline
-1 & 0.378247033596314 \tabularnewline
0 & 0.356723650237328 \tabularnewline
1 & 0.329387830504097 \tabularnewline
2 & 0.283584977427138 \tabularnewline
3 & 0.254143882266375 \tabularnewline
4 & 0.243091560569900 \tabularnewline
5 & 0.222003951551093 \tabularnewline
6 & 0.185118007364811 \tabularnewline
7 & 0.144835923093565 \tabularnewline
8 & 0.129976445747474 \tabularnewline
9 & 0.112434239087552 \tabularnewline
10 & 0.0812196565198096 \tabularnewline
11 & 0.0534264942762935 \tabularnewline
12 & 0.0333791247677876 \tabularnewline
13 & 0.0172798270751182 \tabularnewline
14 & -0.0211603075144018 \tabularnewline
15 & -0.0530531020512435 \tabularnewline
16 & -0.0558156825152876 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7909&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]0.646968800104545[/C][/ROW]
[ROW][C]-15[/C][C]0.646171947072123[/C][/ROW]
[ROW][C]-14[/C][C]0.613097913532082[/C][/ROW]
[ROW][C]-13[/C][C]0.590371602041709[/C][/ROW]
[ROW][C]-12[/C][C]0.58865498374925[/C][/ROW]
[ROW][C]-11[/C][C]0.58971846602711[/C][/ROW]
[ROW][C]-10[/C][C]0.561500778545096[/C][/ROW]
[ROW][C]-9[/C][C]0.553220611816891[/C][/ROW]
[ROW][C]-8[/C][C]0.55804431800832[/C][/ROW]
[ROW][C]-7[/C][C]0.535639392143397[/C][/ROW]
[ROW][C]-6[/C][C]0.514902236321267[/C][/ROW]
[ROW][C]-5[/C][C]0.483165394384291[/C][/ROW]
[ROW][C]-4[/C][C]0.482265485065501[/C][/ROW]
[ROW][C]-3[/C][C]0.469972050114942[/C][/ROW]
[ROW][C]-2[/C][C]0.418908162867003[/C][/ROW]
[ROW][C]-1[/C][C]0.378247033596314[/C][/ROW]
[ROW][C]0[/C][C]0.356723650237328[/C][/ROW]
[ROW][C]1[/C][C]0.329387830504097[/C][/ROW]
[ROW][C]2[/C][C]0.283584977427138[/C][/ROW]
[ROW][C]3[/C][C]0.254143882266375[/C][/ROW]
[ROW][C]4[/C][C]0.243091560569900[/C][/ROW]
[ROW][C]5[/C][C]0.222003951551093[/C][/ROW]
[ROW][C]6[/C][C]0.185118007364811[/C][/ROW]
[ROW][C]7[/C][C]0.144835923093565[/C][/ROW]
[ROW][C]8[/C][C]0.129976445747474[/C][/ROW]
[ROW][C]9[/C][C]0.112434239087552[/C][/ROW]
[ROW][C]10[/C][C]0.0812196565198096[/C][/ROW]
[ROW][C]11[/C][C]0.0534264942762935[/C][/ROW]
[ROW][C]12[/C][C]0.0333791247677876[/C][/ROW]
[ROW][C]13[/C][C]0.0172798270751182[/C][/ROW]
[ROW][C]14[/C][C]-0.0211603075144018[/C][/ROW]
[ROW][C]15[/C][C]-0.0530531020512435[/C][/ROW]
[ROW][C]16[/C][C]-0.0558156825152876[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7909&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7909&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])
-160.646968800104545
-150.646171947072123
-140.613097913532082
-130.590371602041709
-120.58865498374925
-110.58971846602711
-100.561500778545096
-90.553220611816891
-80.55804431800832
-70.535639392143397
-60.514902236321267
-50.483165394384291
-40.482265485065501
-30.469972050114942
-20.418908162867003
-10.378247033596314
00.356723650237328
10.329387830504097
20.283584977427138
30.254143882266375
40.243091560569900
50.222003951551093
60.185118007364811
70.144835923093565
80.129976445747474
90.112434239087552
100.0812196565198096
110.0534264942762935
120.0333791247677876
130.0172798270751182
14-0.0211603075144018
15-0.0530531020512435
16-0.0558156825152876


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')