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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 computationMon, 22 Dec 2008 07:39:39 -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/22/t12299568547wmkf0fnl3bysow.htm/, Retrieved Sun, 12 May 2024 18:34:27 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=36089, Retrieved Sun, 12 May 2024 18:34:27 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact144

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Spectral Analysis] [] [2008-12-16 12:03:12] [36e149b0e818e09d2b19e9807cb730e0]
- RMPD    [Cross Correlation Function] [] [2008-12-22 14:39:39] [a5ed2c45dea395ef181ba16fe56905d7] [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
92.5
104.2
112.5
122.4
113.3
100.0
Dataseries Y:
Download CSV
Histogram 
108.65
107.03
104.21
108.65
101.45
100.34
112.6
118.56
119.32
116.97
109.56
109.58
110.74
110.41
109.44
107.3
105.78
105.99
120.23
122.17
121.66
120.64
118.46
119.16
120.77
120.27
118.62
118.44
116.51
117.94
132.44
134.86
134.46
131.54
127.33
129.06
130.81
130.47
129.19
126.46
124.84
126.25
138.07
142.08
142.51
142.21
138.22
138.52
137.45
137.11
135.95
133.32
132.01
132.37
144.4
146.3
146.14
142.4
138.51
138.91
138.04
137.27
134.88
133.58
133.24
133.28
144.13
145.58
144.21
136.7
131.61
129.64
130.41
127.68
123.68
122.34
118.88
116
129.19
131.34
126
122.61
118.6
119.63

Tables (Output of Computation)





Summary of computational 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 computational 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=36089&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]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=36089&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36089&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 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])
-15-0.0555583432489202
-14-0.0192958495216961
-130.0915578891178058
-12-0.0790591455818946
-110.0649649942882044
-10-0.0142141801921136
-9-0.151031624143315
-8-0.105332774866442
-7-0.0360548385165333
-6-0.0873158210407789
-50.112665623227930
-4-0.0565674583937981
-3-0.220069997985517
-20.0888530566492774
-1-0.00548879362819049
0-0.0609164356125226
10.00300850316253011
2-0.146578506807338
30.0318246702173130
4-0.01994572597659
5-0.098048890870901
6-0.288570567886966
7-0.00800778624440274
8-0.138464628344262
90.0184938125384904
10-0.0691708501744354
11-0.110203982121613
12-0.0224992057178561
13-0.149728806927567
14-0.0569263480839953
15-0.0465611730169693

\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 & -0.0555583432489202 \tabularnewline
-14 & -0.0192958495216961 \tabularnewline
-13 & 0.0915578891178058 \tabularnewline
-12 & -0.0790591455818946 \tabularnewline
-11 & 0.0649649942882044 \tabularnewline
-10 & -0.0142141801921136 \tabularnewline
-9 & -0.151031624143315 \tabularnewline
-8 & -0.105332774866442 \tabularnewline
-7 & -0.0360548385165333 \tabularnewline
-6 & -0.0873158210407789 \tabularnewline
-5 & 0.112665623227930 \tabularnewline
-4 & -0.0565674583937981 \tabularnewline
-3 & -0.220069997985517 \tabularnewline
-2 & 0.0888530566492774 \tabularnewline
-1 & -0.00548879362819049 \tabularnewline
0 & -0.0609164356125226 \tabularnewline
1 & 0.00300850316253011 \tabularnewline
2 & -0.146578506807338 \tabularnewline
3 & 0.0318246702173130 \tabularnewline
4 & -0.01994572597659 \tabularnewline
5 & -0.098048890870901 \tabularnewline
6 & -0.288570567886966 \tabularnewline
7 & -0.00800778624440274 \tabularnewline
8 & -0.138464628344262 \tabularnewline
9 & 0.0184938125384904 \tabularnewline
10 & -0.0691708501744354 \tabularnewline
11 & -0.110203982121613 \tabularnewline
12 & -0.0224992057178561 \tabularnewline
13 & -0.149728806927567 \tabularnewline
14 & -0.0569263480839953 \tabularnewline
15 & -0.0465611730169693 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=36089&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]-0.0555583432489202[/C][/ROW]
[ROW][C]-14[/C][C]-0.0192958495216961[/C][/ROW]
[ROW][C]-13[/C][C]0.0915578891178058[/C][/ROW]
[ROW][C]-12[/C][C]-0.0790591455818946[/C][/ROW]
[ROW][C]-11[/C][C]0.0649649942882044[/C][/ROW]
[ROW][C]-10[/C][C]-0.0142141801921136[/C][/ROW]
[ROW][C]-9[/C][C]-0.151031624143315[/C][/ROW]
[ROW][C]-8[/C][C]-0.105332774866442[/C][/ROW]
[ROW][C]-7[/C][C]-0.0360548385165333[/C][/ROW]
[ROW][C]-6[/C][C]-0.0873158210407789[/C][/ROW]
[ROW][C]-5[/C][C]0.112665623227930[/C][/ROW]
[ROW][C]-4[/C][C]-0.0565674583937981[/C][/ROW]
[ROW][C]-3[/C][C]-0.220069997985517[/C][/ROW]
[ROW][C]-2[/C][C]0.0888530566492774[/C][/ROW]
[ROW][C]-1[/C][C]-0.00548879362819049[/C][/ROW]
[ROW][C]0[/C][C]-0.0609164356125226[/C][/ROW]
[ROW][C]1[/C][C]0.00300850316253011[/C][/ROW]
[ROW][C]2[/C][C]-0.146578506807338[/C][/ROW]
[ROW][C]3[/C][C]0.0318246702173130[/C][/ROW]
[ROW][C]4[/C][C]-0.01994572597659[/C][/ROW]
[ROW][C]5[/C][C]-0.098048890870901[/C][/ROW]
[ROW][C]6[/C][C]-0.288570567886966[/C][/ROW]
[ROW][C]7[/C][C]-0.00800778624440274[/C][/ROW]
[ROW][C]8[/C][C]-0.138464628344262[/C][/ROW]
[ROW][C]9[/C][C]0.0184938125384904[/C][/ROW]
[ROW][C]10[/C][C]-0.0691708501744354[/C][/ROW]
[ROW][C]11[/C][C]-0.110203982121613[/C][/ROW]
[ROW][C]12[/C][C]-0.0224992057178561[/C][/ROW]
[ROW][C]13[/C][C]-0.149728806927567[/C][/ROW]
[ROW][C]14[/C][C]-0.0569263480839953[/C][/ROW]
[ROW][C]15[/C][C]-0.0465611730169693[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=36089&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=36089&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])
-15-0.0555583432489202
-14-0.0192958495216961
-130.0915578891178058
-12-0.0790591455818946
-110.0649649942882044
-10-0.0142141801921136
-9-0.151031624143315
-8-0.105332774866442
-7-0.0360548385165333
-6-0.0873158210407789
-50.112665623227930
-4-0.0565674583937981
-3-0.220069997985517
-20.0888530566492774
-1-0.00548879362819049
0-0.0609164356125226
10.00300850316253011
2-0.146578506807338
30.0318246702173130
4-0.01994572597659
5-0.098048890870901
6-0.288570567886966
7-0.00800778624440274
8-0.138464628344262
90.0184938125384904
10-0.0691708501744354
11-0.110203982121613
12-0.0224992057178561
13-0.149728806927567
14-0.0569263480839953
15-0.0465611730169693


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) 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')