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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, 02 Dec 2008 13:11:37 -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/02/t12282487301oxhi0uyekfeute.htm/, Retrieved Sat, 25 May 2024 06:24:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28337, Retrieved Sat, 25 May 2024 06:24:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact140

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] [Toon Wouters] [2008-12-02 20:11:37] [14e94996a4178d938cb12bed20a4a373] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
103.1
100.6
103.1
95.5
90.5
90.9
88.8
90.7
94.3
104.6
111.1
110.8
107.2
99
99
91
96.2
96.9
96.2
100.1
99
115.4
106.9
107.1
99.3
99.2
108.3
105.6
99.5
107.4
93.1
88.1
110.7
113.1
99.6
93.6
98.6
99.6
114.3
107.8
101.2
112.5
100.5
93.9
116.2
112
106.4
95.7
96
95.8
103
102.2
98.4
111.4
86.6
91.3
107.9
101.8
104.4
93.4
100.1
98.5
112.9
101.4
107.1
110.8
90.3
95.5
111.4
113
107.5
95.9
106.3
105.2
117.2
106.9
108.2
113
97.2
99.9
108.1
118.1
109.1
93.3
Dataseries Y:
Download CSV
Histogram 
119.5
125
145
105.3
116.9
120.1
88.9
78.4
114.6
113.3
117
99.6
99.4
101.9
115.2
108.5
113.8
121
92.2
90.2
101.5
126.6
93.9
89.8
93.4
101.5
110.4
105.9
108.4
113.9
86.1
69.4
101.2
100.5
98
106.6
90.1
96.9
125.9
112
100
123.9
79.8
83.4
113.6
112.9
104
109.9
99
106.3
128.9
111.1
102.9
130
87
87.5
117.6
103.4
110.8
112.6
102.5
112.4
135.6
105.1
127.7
137
91
90.5
122.4
123.3
124.3
120
118.1
119
142.7
123.6
129.6
151.6
110.4
99.2
130.5
136.2
129.7
128

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28337&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]0 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=28337&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28337&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series0.8
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 series0.3
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-15-0.176229238326033
-14-0.158910608353522
-13-0.190572326980891
-12-0.139641377262342
-11-0.0176993149672778
-10-0.197178364209623
-90.170925194791631
-80.0260244317221500
-70.0669920149610879
-60.0839470587967847
-50.00302924082915931
-4-0.240775395035468
-30.0778644290786383
-20.117253167994326
-1-0.0265154037074874
00.276792800375996
10.0698000398500585
20.172098356230071
30.0577100901388899
4-0.0288957582201914
5-0.200034842168454
6-0.100431605122844
7-0.176320943625117
80.0956618251197688
90.00634858880478325
10-0.0263907719694891
110.04780091340891
12-0.0644565252664648
13-0.155303339671979
14-0.0975011115385587
15-0.149418963240883

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0.8 \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 & 0.3 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & -0.176229238326033 \tabularnewline
-14 & -0.158910608353522 \tabularnewline
-13 & -0.190572326980891 \tabularnewline
-12 & -0.139641377262342 \tabularnewline
-11 & -0.0176993149672778 \tabularnewline
-10 & -0.197178364209623 \tabularnewline
-9 & 0.170925194791631 \tabularnewline
-8 & 0.0260244317221500 \tabularnewline
-7 & 0.0669920149610879 \tabularnewline
-6 & 0.0839470587967847 \tabularnewline
-5 & 0.00302924082915931 \tabularnewline
-4 & -0.240775395035468 \tabularnewline
-3 & 0.0778644290786383 \tabularnewline
-2 & 0.117253167994326 \tabularnewline
-1 & -0.0265154037074874 \tabularnewline
0 & 0.276792800375996 \tabularnewline
1 & 0.0698000398500585 \tabularnewline
2 & 0.172098356230071 \tabularnewline
3 & 0.0577100901388899 \tabularnewline
4 & -0.0288957582201914 \tabularnewline
5 & -0.200034842168454 \tabularnewline
6 & -0.100431605122844 \tabularnewline
7 & -0.176320943625117 \tabularnewline
8 & 0.0956618251197688 \tabularnewline
9 & 0.00634858880478325 \tabularnewline
10 & -0.0263907719694891 \tabularnewline
11 & 0.04780091340891 \tabularnewline
12 & -0.0644565252664648 \tabularnewline
13 & -0.155303339671979 \tabularnewline
14 & -0.0975011115385587 \tabularnewline
15 & -0.149418963240883 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28337&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]0.8[/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]0.3[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]-0.176229238326033[/C][/ROW]
[ROW][C]-14[/C][C]-0.158910608353522[/C][/ROW]
[ROW][C]-13[/C][C]-0.190572326980891[/C][/ROW]
[ROW][C]-12[/C][C]-0.139641377262342[/C][/ROW]
[ROW][C]-11[/C][C]-0.0176993149672778[/C][/ROW]
[ROW][C]-10[/C][C]-0.197178364209623[/C][/ROW]
[ROW][C]-9[/C][C]0.170925194791631[/C][/ROW]
[ROW][C]-8[/C][C]0.0260244317221500[/C][/ROW]
[ROW][C]-7[/C][C]0.0669920149610879[/C][/ROW]
[ROW][C]-6[/C][C]0.0839470587967847[/C][/ROW]
[ROW][C]-5[/C][C]0.00302924082915931[/C][/ROW]
[ROW][C]-4[/C][C]-0.240775395035468[/C][/ROW]
[ROW][C]-3[/C][C]0.0778644290786383[/C][/ROW]
[ROW][C]-2[/C][C]0.117253167994326[/C][/ROW]
[ROW][C]-1[/C][C]-0.0265154037074874[/C][/ROW]
[ROW][C]0[/C][C]0.276792800375996[/C][/ROW]
[ROW][C]1[/C][C]0.0698000398500585[/C][/ROW]
[ROW][C]2[/C][C]0.172098356230071[/C][/ROW]
[ROW][C]3[/C][C]0.0577100901388899[/C][/ROW]
[ROW][C]4[/C][C]-0.0288957582201914[/C][/ROW]
[ROW][C]5[/C][C]-0.200034842168454[/C][/ROW]
[ROW][C]6[/C][C]-0.100431605122844[/C][/ROW]
[ROW][C]7[/C][C]-0.176320943625117[/C][/ROW]
[ROW][C]8[/C][C]0.0956618251197688[/C][/ROW]
[ROW][C]9[/C][C]0.00634858880478325[/C][/ROW]
[ROW][C]10[/C][C]-0.0263907719694891[/C][/ROW]
[ROW][C]11[/C][C]0.04780091340891[/C][/ROW]
[ROW][C]12[/C][C]-0.0644565252664648[/C][/ROW]
[ROW][C]13[/C][C]-0.155303339671979[/C][/ROW]
[ROW][C]14[/C][C]-0.0975011115385587[/C][/ROW]
[ROW][C]15[/C][C]-0.149418963240883[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28337&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28337&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 series0.8
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 series0.3
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-15-0.176229238326033
-14-0.158910608353522
-13-0.190572326980891
-12-0.139641377262342
-11-0.0176993149672778
-10-0.197178364209623
-90.170925194791631
-80.0260244317221500
-70.0669920149610879
-60.0839470587967847
-50.00302924082915931
-4-0.240775395035468
-30.0778644290786383
-20.117253167994326
-1-0.0265154037074874
00.276792800375996
10.0698000398500585
20.172098356230071
30.0577100901388899
4-0.0288957582201914
5-0.200034842168454
6-0.100431605122844
7-0.176320943625117
80.0956618251197688
90.00634858880478325
10-0.0263907719694891
110.04780091340891
12-0.0644565252664648
13-0.155303339671979
14-0.0975011115385587
15-0.149418963240883


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.8 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 0.3 ; par6 = 0 ; par7 = 1 ;
Parameters (R input):
par1 = 0.8 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 0.3 ; par6 = 0 ; 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')