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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 computationTue, 09 Dec 2008 05:48:40 -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/09/t122882702770zepvu2lj1teb0.htm/, Retrieved Sun, 19 May 2024 11:15:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=31345, Retrieved Sun, 19 May 2024 11:15:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

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] [] [2008-12-09 12:48:40] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
130.5
104.7
115.2
124.5
112.3
127.5
120.6
117.5
117.7
120.4
125.0
131.6
121.1
114.2
112.1
127.0
116.8
112.0
129.7
113.6
115.7
119.5
125.8
129.6
128.0
112.8
101.6
123.9
118.8
109.1
130.6
112.4
111.0
116.2
119.8
117.2
127.3
107.7
97.5
120.1
110.6
111.3
119.8
105.5
108.7
128.7
119.5
121.1
128.4
108.8
107.5
125.6
102.9
107.5
120.4
104.3
100.6
121.9
112.7
124.9
Dataseries Y:
Download CSV
Histogram 
143.6
104.5
123.3
156.6
136.2
147.5
143.8
135.8
121.6
128.0
129.7
136.2
130.5
99.2
110.4
151.6
129.6
123.6
142.7
119.0
118.1
120.0
124.3
123.3
122.4
90.5
91.0
137.0
127.7
105.1
135.6
112.4
102.5
112.6
110.8
103.4
117.6
87.5
87.0
130.0
102.9
111.1
128.9
106.3
99.0
109.9
104.0
112.9
113.6
83.4
79.8
123.9
100.0
112.0
125.9
96.9
90.1
106.6
98.0
100.5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 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=31345&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]2 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=31345&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31345&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 time2 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])
-14-0.222977732950706
-13-0.0725250487135264
-120.430188337127877
-11-0.00798635569298515
-10-0.125326774298093
-90.234907340082525
-8-0.0358109269443656
-70.092380966664422
-60.441315557626156
-50.091363210082016
-4-0.0163323998927554
-30.268786137812814
-2-0.169913013346546
-1-0.0427479977330030
00.705079038648071
10.0313151815089949
2-0.0359886158769701
30.414184133143513
40.0466324253105123
50.150045074879415
60.542537042863407
70.140148939174185
80.058646808088004
90.185631064375708
10-0.205294799708988
11-0.0583404933113539
120.458999965609255
130.0275811106851698
14-0.118338218547475

\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 & -0.222977732950706 \tabularnewline
-13 & -0.0725250487135264 \tabularnewline
-12 & 0.430188337127877 \tabularnewline
-11 & -0.00798635569298515 \tabularnewline
-10 & -0.125326774298093 \tabularnewline
-9 & 0.234907340082525 \tabularnewline
-8 & -0.0358109269443656 \tabularnewline
-7 & 0.092380966664422 \tabularnewline
-6 & 0.441315557626156 \tabularnewline
-5 & 0.091363210082016 \tabularnewline
-4 & -0.0163323998927554 \tabularnewline
-3 & 0.268786137812814 \tabularnewline
-2 & -0.169913013346546 \tabularnewline
-1 & -0.0427479977330030 \tabularnewline
0 & 0.705079038648071 \tabularnewline
1 & 0.0313151815089949 \tabularnewline
2 & -0.0359886158769701 \tabularnewline
3 & 0.414184133143513 \tabularnewline
4 & 0.0466324253105123 \tabularnewline
5 & 0.150045074879415 \tabularnewline
6 & 0.542537042863407 \tabularnewline
7 & 0.140148939174185 \tabularnewline
8 & 0.058646808088004 \tabularnewline
9 & 0.185631064375708 \tabularnewline
10 & -0.205294799708988 \tabularnewline
11 & -0.0583404933113539 \tabularnewline
12 & 0.458999965609255 \tabularnewline
13 & 0.0275811106851698 \tabularnewline
14 & -0.118338218547475 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=31345&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]-0.222977732950706[/C][/ROW]
[ROW][C]-13[/C][C]-0.0725250487135264[/C][/ROW]
[ROW][C]-12[/C][C]0.430188337127877[/C][/ROW]
[ROW][C]-11[/C][C]-0.00798635569298515[/C][/ROW]
[ROW][C]-10[/C][C]-0.125326774298093[/C][/ROW]
[ROW][C]-9[/C][C]0.234907340082525[/C][/ROW]
[ROW][C]-8[/C][C]-0.0358109269443656[/C][/ROW]
[ROW][C]-7[/C][C]0.092380966664422[/C][/ROW]
[ROW][C]-6[/C][C]0.441315557626156[/C][/ROW]
[ROW][C]-5[/C][C]0.091363210082016[/C][/ROW]
[ROW][C]-4[/C][C]-0.0163323998927554[/C][/ROW]
[ROW][C]-3[/C][C]0.268786137812814[/C][/ROW]
[ROW][C]-2[/C][C]-0.169913013346546[/C][/ROW]
[ROW][C]-1[/C][C]-0.0427479977330030[/C][/ROW]
[ROW][C]0[/C][C]0.705079038648071[/C][/ROW]
[ROW][C]1[/C][C]0.0313151815089949[/C][/ROW]
[ROW][C]2[/C][C]-0.0359886158769701[/C][/ROW]
[ROW][C]3[/C][C]0.414184133143513[/C][/ROW]
[ROW][C]4[/C][C]0.0466324253105123[/C][/ROW]
[ROW][C]5[/C][C]0.150045074879415[/C][/ROW]
[ROW][C]6[/C][C]0.542537042863407[/C][/ROW]
[ROW][C]7[/C][C]0.140148939174185[/C][/ROW]
[ROW][C]8[/C][C]0.058646808088004[/C][/ROW]
[ROW][C]9[/C][C]0.185631064375708[/C][/ROW]
[ROW][C]10[/C][C]-0.205294799708988[/C][/ROW]
[ROW][C]11[/C][C]-0.0583404933113539[/C][/ROW]
[ROW][C]12[/C][C]0.458999965609255[/C][/ROW]
[ROW][C]13[/C][C]0.0275811106851698[/C][/ROW]
[ROW][C]14[/C][C]-0.118338218547475[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=31345&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=31345&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])
-14-0.222977732950706
-13-0.0725250487135264
-120.430188337127877
-11-0.00798635569298515
-10-0.125326774298093
-90.234907340082525
-8-0.0358109269443656
-70.092380966664422
-60.441315557626156
-50.091363210082016
-4-0.0163323998927554
-30.268786137812814
-2-0.169913013346546
-1-0.0427479977330030
00.705079038648071
10.0313151815089949
2-0.0359886158769701
30.414184133143513
40.0466324253105123
50.150045074879415
60.542537042863407
70.140148939174185
80.058646808088004
90.185631064375708
10-0.205294799708988
11-0.0583404933113539
120.458999965609255
130.0275811106851698
14-0.118338218547475


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) 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')