FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSun, 14 Dec 2008 07:18:55 -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/14/t1229264400o9wpy7m6en9pwyt.htm/, Retrieved Wed, 15 May 2024 09:09:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=33390, Retrieved Wed, 15 May 2024 09:09:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact225

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD  [Standard Deviation-Mean Plot] [] [2008-12-01 21:10:18] [cb714085b233acee8e8acd879ea442b6]
- RMPD    [Cross Correlation Function] [] [2008-12-08 20:47:03] [cb714085b233acee8e8acd879ea442b6]
-   PD        [Cross Correlation Function] [] [2008-12-14 14:18:55] [787873b6436f665b5b192a0bdb2e43c9] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
34
39
40
45
43
42
49
43
50
44
40
41
45
45
48
54
47
35
28
28
34
23
33
38
41
47
46
45
47
49
50
56
50
56
58
59
51
59
60
60
68
62
62
58
56
50
52
36
33
26
28
27
20
16
11
0
3
10
0
3
Dataseries Y:
Download CSV
Histogram 
0
9
1
4
6
21
24
23
22
21
20
16
18
18
24
16
15
24
18
15
4
3
6
5
12
12
12
14
12
17
12
20
21
15
22
19
19
26
25
19
20
30
31
35
33
26
25
17
14
8
12
7
4
10
8
16
14
20
9
10

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 4 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=33390&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]4 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=33390&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33390&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1.5
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0.9
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-14-0.189460186973149
-130.0938159506336647
-12-0.113659655043352
-110.194803034039417
-10-0.142151426525548
-90.150904186409036
-8-0.211472740562950
-7-0.0677504306370909
-60.0361336882937673
-5-0.160995583928591
-40.268373328102169
-30.150184118996976
-20.247955698054933
-10.00559003037842649
00.132350274268414
10.083897004960539
20.0709375787247813
30.156483691040883
4-0.266505878520667
5-0.0371924770627967
60.0809940830334304
70.00102877946157767
80.0890057973448534
90.087466274585549
10-0.058680550415518
11-0.0552982268817533
12-0.184205319808935
13-0.147038580881048
140.05394864138413

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 1.5 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 1 \tabularnewline
Degree of seasonal differencing (D) of X series & 0 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 0.9 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & -0.189460186973149 \tabularnewline
-13 & 0.0938159506336647 \tabularnewline
-12 & -0.113659655043352 \tabularnewline
-11 & 0.194803034039417 \tabularnewline
-10 & -0.142151426525548 \tabularnewline
-9 & 0.150904186409036 \tabularnewline
-8 & -0.211472740562950 \tabularnewline
-7 & -0.0677504306370909 \tabularnewline
-6 & 0.0361336882937673 \tabularnewline
-5 & -0.160995583928591 \tabularnewline
-4 & 0.268373328102169 \tabularnewline
-3 & 0.150184118996976 \tabularnewline
-2 & 0.247955698054933 \tabularnewline
-1 & 0.00559003037842649 \tabularnewline
0 & 0.132350274268414 \tabularnewline
1 & 0.083897004960539 \tabularnewline
2 & 0.0709375787247813 \tabularnewline
3 & 0.156483691040883 \tabularnewline
4 & -0.266505878520667 \tabularnewline
5 & -0.0371924770627967 \tabularnewline
6 & 0.0809940830334304 \tabularnewline
7 & 0.00102877946157767 \tabularnewline
8 & 0.0890057973448534 \tabularnewline
9 & 0.087466274585549 \tabularnewline
10 & -0.058680550415518 \tabularnewline
11 & -0.0552982268817533 \tabularnewline
12 & -0.184205319808935 \tabularnewline
13 & -0.147038580881048 \tabularnewline
14 & 0.05394864138413 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=33390&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]1.5[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]1[/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]0.9[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]1[/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]-0.189460186973149[/C][/ROW]
[ROW][C]-13[/C][C]0.0938159506336647[/C][/ROW]
[ROW][C]-12[/C][C]-0.113659655043352[/C][/ROW]
[ROW][C]-11[/C][C]0.194803034039417[/C][/ROW]
[ROW][C]-10[/C][C]-0.142151426525548[/C][/ROW]
[ROW][C]-9[/C][C]0.150904186409036[/C][/ROW]
[ROW][C]-8[/C][C]-0.211472740562950[/C][/ROW]
[ROW][C]-7[/C][C]-0.0677504306370909[/C][/ROW]
[ROW][C]-6[/C][C]0.0361336882937673[/C][/ROW]
[ROW][C]-5[/C][C]-0.160995583928591[/C][/ROW]
[ROW][C]-4[/C][C]0.268373328102169[/C][/ROW]
[ROW][C]-3[/C][C]0.150184118996976[/C][/ROW]
[ROW][C]-2[/C][C]0.247955698054933[/C][/ROW]
[ROW][C]-1[/C][C]0.00559003037842649[/C][/ROW]
[ROW][C]0[/C][C]0.132350274268414[/C][/ROW]
[ROW][C]1[/C][C]0.083897004960539[/C][/ROW]
[ROW][C]2[/C][C]0.0709375787247813[/C][/ROW]
[ROW][C]3[/C][C]0.156483691040883[/C][/ROW]
[ROW][C]4[/C][C]-0.266505878520667[/C][/ROW]
[ROW][C]5[/C][C]-0.0371924770627967[/C][/ROW]
[ROW][C]6[/C][C]0.0809940830334304[/C][/ROW]
[ROW][C]7[/C][C]0.00102877946157767[/C][/ROW]
[ROW][C]8[/C][C]0.0890057973448534[/C][/ROW]
[ROW][C]9[/C][C]0.087466274585549[/C][/ROW]
[ROW][C]10[/C][C]-0.058680550415518[/C][/ROW]
[ROW][C]11[/C][C]-0.0552982268817533[/C][/ROW]
[ROW][C]12[/C][C]-0.184205319808935[/C][/ROW]
[ROW][C]13[/C][C]-0.147038580881048[/C][/ROW]
[ROW][C]14[/C][C]0.05394864138413[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=33390&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=33390&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 series1.5
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0.9
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-14-0.189460186973149
-130.0938159506336647
-12-0.113659655043352
-110.194803034039417
-10-0.142151426525548
-90.150904186409036
-8-0.211472740562950
-7-0.0677504306370909
-60.0361336882937673
-5-0.160995583928591
-40.268373328102169
-30.150184118996976
-20.247955698054933
-10.00559003037842649
00.132350274268414
10.083897004960539
20.0709375787247813
30.156483691040883
4-0.266505878520667
5-0.0371924770627967
60.0809940830334304
70.00102877946157767
80.0890057973448534
90.087466274585549
10-0.058680550415518
11-0.0552982268817533
12-0.184205319808935
13-0.147038580881048
140.05394864138413


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1.5 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 0.9 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1.5 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 0.9 ; par6 = 1 ; 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')