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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, 19 Dec 2007 16:30:06 -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/2007/Dec/20/t1198105949z4ndwyv5vabhjuz.htm/, Retrieved Mon, 29 Apr 2024 11:37:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4705, Retrieved Mon, 29 Apr 2024 11:37:40 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact211

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...] [2007-12-19 23:30:06] [757ef2b8266f339cc1cb96dcaefa4cf0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
98,8
100,5
110,4
96,4
101,9
106,2
81,0
94,7
101,0
109,4
102,3
90,7
96,2
96,1
106,0
103,1
102,0
104,7
86,0
92,1
106,9
112,6
101,7
92,0
97,4
97,0
105,4
102,7
98,1
104,5
87,4
89,9
109,8
111,7
98,6
96,9
95,1
97,0
112,7
102,9
97,4
111,4
87,4
96,8
114,1
110,3
103,9
101,6
94,6
95,9
104,7
102,8
98,1
113,9
80,9
95,7
113,2
105,9
108,8
102,3
99,0
100,7
115,5
100,7
109,9
114,6
85,4
100,5
114,8
116,5
112,9
102,0
106,0
105,3
118,8
106,1
109,3
117,2
91,9
103,9
115,9
Dataseries Y:
Download CSV
Histogram 
106,0
100,9
114,3
101,2
109,2
111,6
91,7
93,7
105,7
109,5
105,3
102,8
100,6
97,6
110,3
107,2
107,2
108,1
97,1
92,2
112,2
111,6
115,7
111,3
104,2
103,2
112,7
106,4
102,6
110,6
95,2
89,0
112,5
116,8
107,2
113,6
101,8
102,6
122,7
110,3
110,5
121,6
100,3
100,7
123,4
127,1
124,1
131,2
111,6
114,2
130,1
125,9
119,0
133,8
107,5
113,5
134,4
126,8
135,6
139,9
129,8
131,0
153,1
134,1
144,1
155,9
123,3
128,1
144,3
153,0
149,9
150,9
141,0
138,9
157,4
142,9
151,7
161,0
138,6
136,0
151,9

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=4705&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=4705&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4705&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 series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.164839462182417
-14-0.162012245003598
-13-0.121821425041959
-120.376651357395363
-11-0.255232743465134
-100.0889640700796144
-90.0291098873364346
-8-0.115804781341936
-70.0560570759745525
-60.0570588176095795
-5-0.0690112779299165
-40.0264144622387143
-30.0601639275356576
-2-0.165430421835140
-10.182243475333819
0-0.228848554344506
10.129184113946934
20.0208155143198943
3-0.0418055051965077
4-0.0170294293900491
5-0.0284498093428907
60.0829566413724403
7-0.0888319455514382
80.100305707230873
9-0.0234429677441336
10-0.060869153099711
110.0363772464526974
120.00349013786994482
130.0101831769777155
140.00926865436583952
15-0.0201455925919847

\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 & 1 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & 0.164839462182417 \tabularnewline
-14 & -0.162012245003598 \tabularnewline
-13 & -0.121821425041959 \tabularnewline
-12 & 0.376651357395363 \tabularnewline
-11 & -0.255232743465134 \tabularnewline
-10 & 0.0889640700796144 \tabularnewline
-9 & 0.0291098873364346 \tabularnewline
-8 & -0.115804781341936 \tabularnewline
-7 & 0.0560570759745525 \tabularnewline
-6 & 0.0570588176095795 \tabularnewline
-5 & -0.0690112779299165 \tabularnewline
-4 & 0.0264144622387143 \tabularnewline
-3 & 0.0601639275356576 \tabularnewline
-2 & -0.165430421835140 \tabularnewline
-1 & 0.182243475333819 \tabularnewline
0 & -0.228848554344506 \tabularnewline
1 & 0.129184113946934 \tabularnewline
2 & 0.0208155143198943 \tabularnewline
3 & -0.0418055051965077 \tabularnewline
4 & -0.0170294293900491 \tabularnewline
5 & -0.0284498093428907 \tabularnewline
6 & 0.0829566413724403 \tabularnewline
7 & -0.0888319455514382 \tabularnewline
8 & 0.100305707230873 \tabularnewline
9 & -0.0234429677441336 \tabularnewline
10 & -0.060869153099711 \tabularnewline
11 & 0.0363772464526974 \tabularnewline
12 & 0.00349013786994482 \tabularnewline
13 & 0.0101831769777155 \tabularnewline
14 & 0.00926865436583952 \tabularnewline
15 & -0.0201455925919847 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4705&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]1[/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]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]0.164839462182417[/C][/ROW]
[ROW][C]-14[/C][C]-0.162012245003598[/C][/ROW]
[ROW][C]-13[/C][C]-0.121821425041959[/C][/ROW]
[ROW][C]-12[/C][C]0.376651357395363[/C][/ROW]
[ROW][C]-11[/C][C]-0.255232743465134[/C][/ROW]
[ROW][C]-10[/C][C]0.0889640700796144[/C][/ROW]
[ROW][C]-9[/C][C]0.0291098873364346[/C][/ROW]
[ROW][C]-8[/C][C]-0.115804781341936[/C][/ROW]
[ROW][C]-7[/C][C]0.0560570759745525[/C][/ROW]
[ROW][C]-6[/C][C]0.0570588176095795[/C][/ROW]
[ROW][C]-5[/C][C]-0.0690112779299165[/C][/ROW]
[ROW][C]-4[/C][C]0.0264144622387143[/C][/ROW]
[ROW][C]-3[/C][C]0.0601639275356576[/C][/ROW]
[ROW][C]-2[/C][C]-0.165430421835140[/C][/ROW]
[ROW][C]-1[/C][C]0.182243475333819[/C][/ROW]
[ROW][C]0[/C][C]-0.228848554344506[/C][/ROW]
[ROW][C]1[/C][C]0.129184113946934[/C][/ROW]
[ROW][C]2[/C][C]0.0208155143198943[/C][/ROW]
[ROW][C]3[/C][C]-0.0418055051965077[/C][/ROW]
[ROW][C]4[/C][C]-0.0170294293900491[/C][/ROW]
[ROW][C]5[/C][C]-0.0284498093428907[/C][/ROW]
[ROW][C]6[/C][C]0.0829566413724403[/C][/ROW]
[ROW][C]7[/C][C]-0.0888319455514382[/C][/ROW]
[ROW][C]8[/C][C]0.100305707230873[/C][/ROW]
[ROW][C]9[/C][C]-0.0234429677441336[/C][/ROW]
[ROW][C]10[/C][C]-0.060869153099711[/C][/ROW]
[ROW][C]11[/C][C]0.0363772464526974[/C][/ROW]
[ROW][C]12[/C][C]0.00349013786994482[/C][/ROW]
[ROW][C]13[/C][C]0.0101831769777155[/C][/ROW]
[ROW][C]14[/C][C]0.00926865436583952[/C][/ROW]
[ROW][C]15[/C][C]-0.0201455925919847[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4705&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4705&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 series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.164839462182417
-14-0.162012245003598
-13-0.121821425041959
-120.376651357395363
-11-0.255232743465134
-100.0889640700796144
-90.0291098873364346
-8-0.115804781341936
-70.0560570759745525
-60.0570588176095795
-5-0.0690112779299165
-40.0264144622387143
-30.0601639275356576
-2-0.165430421835140
-10.182243475333819
0-0.228848554344506
10.129184113946934
20.0208155143198943
3-0.0418055051965077
4-0.0170294293900491
5-0.0284498093428907
60.0829566413724403
7-0.0888319455514382
80.100305707230873
9-0.0234429677441336
10-0.060869153099711
110.0363772464526974
120.00349013786994482
130.0101831769777155
140.00926865436583952
15-0.0201455925919847


Figures (Output of Computation)

Input Parameters & R Code

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