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Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationFri, 23 Nov 2007 08:45:47 -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/Nov/23/t1195832539pwlim6o8wipzlw9.htm/, Retrieved Mon, 29 Apr 2024 06:13:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6202, Retrieved Mon, 29 Apr 2024 06:13:46 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact208
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Cross Correlation Function] [] [2007-11-23 15:45:47] [2467046df5c61f7ccf2ce4e184abae94] [Current]
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Dataseries X:
92.4
92
95.6
95.8
96.4
99
107
109.7
116.2
115.9
113.8
112.6
113.7
115.9
110.3
111.3
113.4
108.2
104.8
106
110.9
115
118.4
121.4
128.8
131.7
141.7
142.9
139.4
134.7
125
113.6
111.5
108.5
112.3
116.6
115.5
120.1
132.9
128.1
129.3
132.5
131
124.9
120.8
122
122.1
127.4
135.2
137.3
135
136
138.4
134.7
138.4
133.9
133.6
141.2
151.8
155.4
Dataseries Y:
99.7
99
98.1
97
98.5
103.8
114.4
124.5
134.2
131.8
125.6
119.9
114.9
115.5
112.5
111.4
115.3
110.8
103.7
111.1
113
111.2
117.6
121.7
127.3
129.8
137.1
141.4
137.4
130.7
117.2
110.8
111.4
108.2
108.8
110.2
109.5
109.5
116
111.2
112.1
114
119.1
114.1
115.1
115.4
110.8
116
119.2
126.5
127.8
131.3
140.3
137.3
143
134.5
139.9
159.3
170.4
175




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=6202&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=6202&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6202&T=0

As an alternative you can also use a 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 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])
-140.170495180801813
-130.144230998108488
-120.137973670041207
-110.142654014837465
-100.130310151426536
-90.093920027928841
-80.0620663008243898
-70.0809031662580437
-60.121034085705948
-50.210942709447765
-40.316909069832869
-30.427760397330977
-20.553482527391559
-10.70352990477677
00.828893545680003
10.687501555216826
20.510112335711335
30.343305780273967
40.220411533370774
50.122818709983067
60.0217887975594757
7-0.0422599886915047
8-0.102087369121626
9-0.107474167998207
10-0.0928194155347422
11-0.0791766406643956
12-0.0443257874100468
13-0.00133848939092940
140.0419563158285009

\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 & 0.170495180801813 \tabularnewline
-13 & 0.144230998108488 \tabularnewline
-12 & 0.137973670041207 \tabularnewline
-11 & 0.142654014837465 \tabularnewline
-10 & 0.130310151426536 \tabularnewline
-9 & 0.093920027928841 \tabularnewline
-8 & 0.0620663008243898 \tabularnewline
-7 & 0.0809031662580437 \tabularnewline
-6 & 0.121034085705948 \tabularnewline
-5 & 0.210942709447765 \tabularnewline
-4 & 0.316909069832869 \tabularnewline
-3 & 0.427760397330977 \tabularnewline
-2 & 0.553482527391559 \tabularnewline
-1 & 0.70352990477677 \tabularnewline
0 & 0.828893545680003 \tabularnewline
1 & 0.687501555216826 \tabularnewline
2 & 0.510112335711335 \tabularnewline
3 & 0.343305780273967 \tabularnewline
4 & 0.220411533370774 \tabularnewline
5 & 0.122818709983067 \tabularnewline
6 & 0.0217887975594757 \tabularnewline
7 & -0.0422599886915047 \tabularnewline
8 & -0.102087369121626 \tabularnewline
9 & -0.107474167998207 \tabularnewline
10 & -0.0928194155347422 \tabularnewline
11 & -0.0791766406643956 \tabularnewline
12 & -0.0443257874100468 \tabularnewline
13 & -0.00133848939092940 \tabularnewline
14 & 0.0419563158285009 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6202&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]0.170495180801813[/C][/ROW]
[ROW][C]-13[/C][C]0.144230998108488[/C][/ROW]
[ROW][C]-12[/C][C]0.137973670041207[/C][/ROW]
[ROW][C]-11[/C][C]0.142654014837465[/C][/ROW]
[ROW][C]-10[/C][C]0.130310151426536[/C][/ROW]
[ROW][C]-9[/C][C]0.093920027928841[/C][/ROW]
[ROW][C]-8[/C][C]0.0620663008243898[/C][/ROW]
[ROW][C]-7[/C][C]0.0809031662580437[/C][/ROW]
[ROW][C]-6[/C][C]0.121034085705948[/C][/ROW]
[ROW][C]-5[/C][C]0.210942709447765[/C][/ROW]
[ROW][C]-4[/C][C]0.316909069832869[/C][/ROW]
[ROW][C]-3[/C][C]0.427760397330977[/C][/ROW]
[ROW][C]-2[/C][C]0.553482527391559[/C][/ROW]
[ROW][C]-1[/C][C]0.70352990477677[/C][/ROW]
[ROW][C]0[/C][C]0.828893545680003[/C][/ROW]
[ROW][C]1[/C][C]0.687501555216826[/C][/ROW]
[ROW][C]2[/C][C]0.510112335711335[/C][/ROW]
[ROW][C]3[/C][C]0.343305780273967[/C][/ROW]
[ROW][C]4[/C][C]0.220411533370774[/C][/ROW]
[ROW][C]5[/C][C]0.122818709983067[/C][/ROW]
[ROW][C]6[/C][C]0.0217887975594757[/C][/ROW]
[ROW][C]7[/C][C]-0.0422599886915047[/C][/ROW]
[ROW][C]8[/C][C]-0.102087369121626[/C][/ROW]
[ROW][C]9[/C][C]-0.107474167998207[/C][/ROW]
[ROW][C]10[/C][C]-0.0928194155347422[/C][/ROW]
[ROW][C]11[/C][C]-0.0791766406643956[/C][/ROW]
[ROW][C]12[/C][C]-0.0443257874100468[/C][/ROW]
[ROW][C]13[/C][C]-0.00133848939092940[/C][/ROW]
[ROW][C]14[/C][C]0.0419563158285009[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6202&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6202&T=1

As an alternative you can also use a 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])
-140.170495180801813
-130.144230998108488
-120.137973670041207
-110.142654014837465
-100.130310151426536
-90.093920027928841
-80.0620663008243898
-70.0809031662580437
-60.121034085705948
-50.210942709447765
-40.316909069832869
-30.427760397330977
-20.553482527391559
-10.70352990477677
00.828893545680003
10.687501555216826
20.510112335711335
30.343305780273967
40.220411533370774
50.122818709983067
60.0217887975594757
7-0.0422599886915047
8-0.102087369121626
9-0.107474167998207
10-0.0928194155347422
11-0.0791766406643956
12-0.0443257874100468
13-0.00133848939092940
140.0419563158285009



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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')