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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, 26 Nov 2007 13:08:03 -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/26/t1196107285ignok6a4kdctwb0.htm/, Retrieved Fri, 03 May 2024 01:38:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6670, Retrieved Fri, 03 May 2024 01:38:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

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] [opdr 7 q 5 cross ...] [2007-11-26 20:08:03] [0c12eff582f43eaf43ae2f09e879befe] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
112.6
113.8
107.8
103.2
103.3
101.2
107.7
110.4
101.9
115.9
89.9
88.6
117.2
123.9
100
103.6
94.1
98.7
119.5
112.7
104.4
124.7
89.1
97
121.6
118.8
114
111.5
97.2
102.5
113.4
109.8
104.9
126.1
80
96.8
117.2
112.3
117.3
111.1
102.2
104.3
122.9
107.6
121.3
131.5
89
104.4
128.9
135.9
133.3
121.3
120.5
120.4
137.9
126.1
133.2
146.6
103.4
117.2
Dataseries Y:
Download CSV
Histogram 
105.1
113.3
99.1
100.3
93.5
98.8
106.2
98.3
102.1
117.1
101.5
80.5
105.9
109.5
97.2
114.5
93.5
100.9
121.1
116.5
109.3
118.1
108.3
105.4
116.2
111.2
105.8
122.7
99.5
107.9
124.6
115
110.3
132.7
99.7
96.5
118.7
112.9
130.5
137.9
115
116.8
140.9
120.7
134.2
147.3
112.4
107.1
128.4
137.7
135
151
137.4
132.4
161.3
139.8
146
154.6
142.1
120.5

Tables (Output of Computation)





Summary of compuational 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 compuational 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=6670&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]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=6670&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6670&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 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 series1
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])
-130.0244380436589544
-120.11165535871236
-11-0.0885191319818823
-100.136999390286816
-90.151397693171807
-80.133112051571252
-70.313022163836049
-60.264254561829175
-50.179359014096913
-40.398055708939091
-30.34100018161294
-20.294723390644645
-10.495893575710116
00.340126709693640
10.355347642107972
20.42826566851257
30.206392122059104
40.191271731363932
50.312411857842481
60.167622124068613
70.239131450559941
80.280853144408155
90.115771877707910
100.162550839761293
110.219732307888800
120.102315001023881
130.227447348846461

\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 & 0 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & 0.0244380436589544 \tabularnewline
-12 & 0.11165535871236 \tabularnewline
-11 & -0.0885191319818823 \tabularnewline
-10 & 0.136999390286816 \tabularnewline
-9 & 0.151397693171807 \tabularnewline
-8 & 0.133112051571252 \tabularnewline
-7 & 0.313022163836049 \tabularnewline
-6 & 0.264254561829175 \tabularnewline
-5 & 0.179359014096913 \tabularnewline
-4 & 0.398055708939091 \tabularnewline
-3 & 0.34100018161294 \tabularnewline
-2 & 0.294723390644645 \tabularnewline
-1 & 0.495893575710116 \tabularnewline
0 & 0.340126709693640 \tabularnewline
1 & 0.355347642107972 \tabularnewline
2 & 0.42826566851257 \tabularnewline
3 & 0.206392122059104 \tabularnewline
4 & 0.191271731363932 \tabularnewline
5 & 0.312411857842481 \tabularnewline
6 & 0.167622124068613 \tabularnewline
7 & 0.239131450559941 \tabularnewline
8 & 0.280853144408155 \tabularnewline
9 & 0.115771877707910 \tabularnewline
10 & 0.162550839761293 \tabularnewline
11 & 0.219732307888800 \tabularnewline
12 & 0.102315001023881 \tabularnewline
13 & 0.227447348846461 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6670&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]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]-13[/C][C]0.0244380436589544[/C][/ROW]
[ROW][C]-12[/C][C]0.11165535871236[/C][/ROW]
[ROW][C]-11[/C][C]-0.0885191319818823[/C][/ROW]
[ROW][C]-10[/C][C]0.136999390286816[/C][/ROW]
[ROW][C]-9[/C][C]0.151397693171807[/C][/ROW]
[ROW][C]-8[/C][C]0.133112051571252[/C][/ROW]
[ROW][C]-7[/C][C]0.313022163836049[/C][/ROW]
[ROW][C]-6[/C][C]0.264254561829175[/C][/ROW]
[ROW][C]-5[/C][C]0.179359014096913[/C][/ROW]
[ROW][C]-4[/C][C]0.398055708939091[/C][/ROW]
[ROW][C]-3[/C][C]0.34100018161294[/C][/ROW]
[ROW][C]-2[/C][C]0.294723390644645[/C][/ROW]
[ROW][C]-1[/C][C]0.495893575710116[/C][/ROW]
[ROW][C]0[/C][C]0.340126709693640[/C][/ROW]
[ROW][C]1[/C][C]0.355347642107972[/C][/ROW]
[ROW][C]2[/C][C]0.42826566851257[/C][/ROW]
[ROW][C]3[/C][C]0.206392122059104[/C][/ROW]
[ROW][C]4[/C][C]0.191271731363932[/C][/ROW]
[ROW][C]5[/C][C]0.312411857842481[/C][/ROW]
[ROW][C]6[/C][C]0.167622124068613[/C][/ROW]
[ROW][C]7[/C][C]0.239131450559941[/C][/ROW]
[ROW][C]8[/C][C]0.280853144408155[/C][/ROW]
[ROW][C]9[/C][C]0.115771877707910[/C][/ROW]
[ROW][C]10[/C][C]0.162550839761293[/C][/ROW]
[ROW][C]11[/C][C]0.219732307888800[/C][/ROW]
[ROW][C]12[/C][C]0.102315001023881[/C][/ROW]
[ROW][C]13[/C][C]0.227447348846461[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6670&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6670&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 series0
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-130.0244380436589544
-120.11165535871236
-11-0.0885191319818823
-100.136999390286816
-90.151397693171807
-80.133112051571252
-70.313022163836049
-60.264254561829175
-50.179359014096913
-40.398055708939091
-30.34100018161294
-20.294723390644645
-10.495893575710116
00.340126709693640
10.355347642107972
20.42826566851257
30.206392122059104
40.191271731363932
50.312411857842481
60.167622124068613
70.239131450559941
80.280853144408155
90.115771877707910
100.162550839761293
110.219732307888800
120.102315001023881
130.227447348846461


Figures (Output of Computation)

Input Parameters & R Code

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