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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 14:18:59 -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/t1196111358rvihmj4lj4evpb3.htm/, Retrieved Thu, 02 May 2024 17:32:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6715, Retrieved Thu, 02 May 2024 17:32:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact185

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] [] [2007-11-26 21:18:59] [a5d60d21ad00400c5f1209c78aa5829c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105.3
103
103.8
103.4
105.8
101.4
97
94.3
96.6
97.1
95.7
96.9
97.4
95.3
93.6
91.5
93.1
91.7
94.3
93.9
90.9
88.3
91.3
91.7
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
156.6
161.6
160.7
156
159.5
168.7
169.9
169.9
185.9
Dataseries Y:
Download CSV
Histogram 
99.5
101.6
103.9
106.6
108.3
102
93.8
91.6
97.7
94.8
98
103.8
97.8
91.2
89.3
87.5
90.4
94.2
102.2
101.3
96
90.8
93.2
90.9
91.1
90.2
94.3
96
99
103.3
113.1
112.8
112.1
107.4
111
110.5
110.8
112.4
111.5
116.2
122.5
121.3
113.9
110.7
120.8
141.1
147.4
148
158.1
165
187
190.3
182.4
168.8
151.2
120.1
112.5
106.2
107.1
108.5
106.5
108.3
125.6
124
127.2
136.9
135.8
124.3
115.4
113.6
114.4
118.4
117
116.5
115.4
113.6
117.4
116.9
116.4
111.1
110.2
118.9
131.8
130.6
138.3
148.4
148.7
144.3
152.5
162.9
167.2
166.5
185.6

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 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=6715&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]3 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=6715&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6715&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 time3 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 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])
-160.230142633249512
-150.256478322764938
-140.282396958542866
-130.286595498412726
-120.278932540204773
-110.273754886811184
-100.285073789345158
-90.306001275035942
-80.335460415006584
-70.380703953836955
-60.432936949174781
-50.482743741741882
-40.547810370380937
-30.621654637042729
-20.688561866160221
-10.747564748242246
00.80608368042687
10.72167893015031
20.64195833833691
30.554698228219299
40.470606210269613
50.404787646530355
60.359439590224222
70.316102160818641
80.27830097842171
90.255180213235065
100.250396764679693
110.243301585878587
120.246629185502604
130.253293328870881
140.252040273450176
150.236754403967627
160.224088571888619

\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
-16 & 0.230142633249512 \tabularnewline
-15 & 0.256478322764938 \tabularnewline
-14 & 0.282396958542866 \tabularnewline
-13 & 0.286595498412726 \tabularnewline
-12 & 0.278932540204773 \tabularnewline
-11 & 0.273754886811184 \tabularnewline
-10 & 0.285073789345158 \tabularnewline
-9 & 0.306001275035942 \tabularnewline
-8 & 0.335460415006584 \tabularnewline
-7 & 0.380703953836955 \tabularnewline
-6 & 0.432936949174781 \tabularnewline
-5 & 0.482743741741882 \tabularnewline
-4 & 0.547810370380937 \tabularnewline
-3 & 0.621654637042729 \tabularnewline
-2 & 0.688561866160221 \tabularnewline
-1 & 0.747564748242246 \tabularnewline
0 & 0.80608368042687 \tabularnewline
1 & 0.72167893015031 \tabularnewline
2 & 0.64195833833691 \tabularnewline
3 & 0.554698228219299 \tabularnewline
4 & 0.470606210269613 \tabularnewline
5 & 0.404787646530355 \tabularnewline
6 & 0.359439590224222 \tabularnewline
7 & 0.316102160818641 \tabularnewline
8 & 0.27830097842171 \tabularnewline
9 & 0.255180213235065 \tabularnewline
10 & 0.250396764679693 \tabularnewline
11 & 0.243301585878587 \tabularnewline
12 & 0.246629185502604 \tabularnewline
13 & 0.253293328870881 \tabularnewline
14 & 0.252040273450176 \tabularnewline
15 & 0.236754403967627 \tabularnewline
16 & 0.224088571888619 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6715&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]-16[/C][C]0.230142633249512[/C][/ROW]
[ROW][C]-15[/C][C]0.256478322764938[/C][/ROW]
[ROW][C]-14[/C][C]0.282396958542866[/C][/ROW]
[ROW][C]-13[/C][C]0.286595498412726[/C][/ROW]
[ROW][C]-12[/C][C]0.278932540204773[/C][/ROW]
[ROW][C]-11[/C][C]0.273754886811184[/C][/ROW]
[ROW][C]-10[/C][C]0.285073789345158[/C][/ROW]
[ROW][C]-9[/C][C]0.306001275035942[/C][/ROW]
[ROW][C]-8[/C][C]0.335460415006584[/C][/ROW]
[ROW][C]-7[/C][C]0.380703953836955[/C][/ROW]
[ROW][C]-6[/C][C]0.432936949174781[/C][/ROW]
[ROW][C]-5[/C][C]0.482743741741882[/C][/ROW]
[ROW][C]-4[/C][C]0.547810370380937[/C][/ROW]
[ROW][C]-3[/C][C]0.621654637042729[/C][/ROW]
[ROW][C]-2[/C][C]0.688561866160221[/C][/ROW]
[ROW][C]-1[/C][C]0.747564748242246[/C][/ROW]
[ROW][C]0[/C][C]0.80608368042687[/C][/ROW]
[ROW][C]1[/C][C]0.72167893015031[/C][/ROW]
[ROW][C]2[/C][C]0.64195833833691[/C][/ROW]
[ROW][C]3[/C][C]0.554698228219299[/C][/ROW]
[ROW][C]4[/C][C]0.470606210269613[/C][/ROW]
[ROW][C]5[/C][C]0.404787646530355[/C][/ROW]
[ROW][C]6[/C][C]0.359439590224222[/C][/ROW]
[ROW][C]7[/C][C]0.316102160818641[/C][/ROW]
[ROW][C]8[/C][C]0.27830097842171[/C][/ROW]
[ROW][C]9[/C][C]0.255180213235065[/C][/ROW]
[ROW][C]10[/C][C]0.250396764679693[/C][/ROW]
[ROW][C]11[/C][C]0.243301585878587[/C][/ROW]
[ROW][C]12[/C][C]0.246629185502604[/C][/ROW]
[ROW][C]13[/C][C]0.253293328870881[/C][/ROW]
[ROW][C]14[/C][C]0.252040273450176[/C][/ROW]
[ROW][C]15[/C][C]0.236754403967627[/C][/ROW]
[ROW][C]16[/C][C]0.224088571888619[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6715&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6715&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 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])
-160.230142633249512
-150.256478322764938
-140.282396958542866
-130.286595498412726
-120.278932540204773
-110.273754886811184
-100.285073789345158
-90.306001275035942
-80.335460415006584
-70.380703953836955
-60.432936949174781
-50.482743741741882
-40.547810370380937
-30.621654637042729
-20.688561866160221
-10.747564748242246
00.80608368042687
10.72167893015031
20.64195833833691
30.554698228219299
40.470606210269613
50.404787646530355
60.359439590224222
70.316102160818641
80.27830097842171
90.255180213235065
100.250396764679693
110.243301585878587
120.246629185502604
130.253293328870881
140.252040273450176
150.236754403967627
160.224088571888619


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ;
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')