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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 computationSun, 23 Dec 2007 08:14:25 -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/Dec/23/t1198421775z7eaugwpmli6x8o.htm/, Retrieved Sat, 04 May 2024 20:30:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=4836, Retrieved Sat, 04 May 2024 20:30:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact281

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] [cross corr vervoe...] [2007-12-23 15:14:25] [c5caf8a1e3802eaf41184f28719e74c9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.17
101.93
102.05
102.08
102.14
102.15
95.42
95.43
95.43
95.43
95.43
95.57
95.71
94.58
94.6
94.61
94.62
94.66
94.66
94.69
94.79
94.79
94.79
94.79
94.8
95.46
95.49
95.74
95.74
95.74
95.75
95.83
95.83
95.84
95.81
95.81
95.8
97.06
97.15
97.14
97.48
97.48
97.48
97.5
97.63
97.86
97.87
97.87
97.84
98.72
100.49
100.54
100.54
100.54
100.55
100.59
100.60
100.62
100.68
100.68
Dataseries Y:
Download CSV
Histogram 
68.4
70.6
83.9
90.1
90.6
87.1
90.8
94.1
99.8
96.8
87
96.3
107.1
115.2
106.1
89.5
91.3
97.6
100.7
104.6
94.7
101.8
102.5
105.3
110.3
109.8
117.3
118.8
131.3
125.9
133.1
147
145.8
164.4
149.8
137.7
151.7
156.8
180
180.4
170.4
191.6
199.5
218.2
217.5
205
194
199.3
219.3
211.1
215.2
240.2
242.2
240.7
255.4
253
218.2
203.7
205.6
215.6

Tables (Output of Computation)





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=4836&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=4836&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4836&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 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])
-14-0.209251261431644
-13-0.169704350499039
-12-0.131169674095478
-11-0.0948128396805245
-10-0.0558942546245996
-90.00111997796156646
-80.0472344178379564
-70.0854564679371574
-60.133414442029052
-50.191496288904784
-40.256510938769746
-30.308296435529034
-20.354487487730379
-10.393380105398595
00.420297325164524
10.459326336008560
20.504819796398376
30.549232577555124
40.59274471854401
50.632045401807002
60.677290319521592
70.660033965322932
80.634807065278803
90.605282505694044
100.579245810714212
110.558519375427474
120.535099457413163
130.514681628604418
140.480998917157005

\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 & -0.209251261431644 \tabularnewline
-13 & -0.169704350499039 \tabularnewline
-12 & -0.131169674095478 \tabularnewline
-11 & -0.0948128396805245 \tabularnewline
-10 & -0.0558942546245996 \tabularnewline
-9 & 0.00111997796156646 \tabularnewline
-8 & 0.0472344178379564 \tabularnewline
-7 & 0.0854564679371574 \tabularnewline
-6 & 0.133414442029052 \tabularnewline
-5 & 0.191496288904784 \tabularnewline
-4 & 0.256510938769746 \tabularnewline
-3 & 0.308296435529034 \tabularnewline
-2 & 0.354487487730379 \tabularnewline
-1 & 0.393380105398595 \tabularnewline
0 & 0.420297325164524 \tabularnewline
1 & 0.459326336008560 \tabularnewline
2 & 0.504819796398376 \tabularnewline
3 & 0.549232577555124 \tabularnewline
4 & 0.59274471854401 \tabularnewline
5 & 0.632045401807002 \tabularnewline
6 & 0.677290319521592 \tabularnewline
7 & 0.660033965322932 \tabularnewline
8 & 0.634807065278803 \tabularnewline
9 & 0.605282505694044 \tabularnewline
10 & 0.579245810714212 \tabularnewline
11 & 0.558519375427474 \tabularnewline
12 & 0.535099457413163 \tabularnewline
13 & 0.514681628604418 \tabularnewline
14 & 0.480998917157005 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=4836&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]-0.209251261431644[/C][/ROW]
[ROW][C]-13[/C][C]-0.169704350499039[/C][/ROW]
[ROW][C]-12[/C][C]-0.131169674095478[/C][/ROW]
[ROW][C]-11[/C][C]-0.0948128396805245[/C][/ROW]
[ROW][C]-10[/C][C]-0.0558942546245996[/C][/ROW]
[ROW][C]-9[/C][C]0.00111997796156646[/C][/ROW]
[ROW][C]-8[/C][C]0.0472344178379564[/C][/ROW]
[ROW][C]-7[/C][C]0.0854564679371574[/C][/ROW]
[ROW][C]-6[/C][C]0.133414442029052[/C][/ROW]
[ROW][C]-5[/C][C]0.191496288904784[/C][/ROW]
[ROW][C]-4[/C][C]0.256510938769746[/C][/ROW]
[ROW][C]-3[/C][C]0.308296435529034[/C][/ROW]
[ROW][C]-2[/C][C]0.354487487730379[/C][/ROW]
[ROW][C]-1[/C][C]0.393380105398595[/C][/ROW]
[ROW][C]0[/C][C]0.420297325164524[/C][/ROW]
[ROW][C]1[/C][C]0.459326336008560[/C][/ROW]
[ROW][C]2[/C][C]0.504819796398376[/C][/ROW]
[ROW][C]3[/C][C]0.549232577555124[/C][/ROW]
[ROW][C]4[/C][C]0.59274471854401[/C][/ROW]
[ROW][C]5[/C][C]0.632045401807002[/C][/ROW]
[ROW][C]6[/C][C]0.677290319521592[/C][/ROW]
[ROW][C]7[/C][C]0.660033965322932[/C][/ROW]
[ROW][C]8[/C][C]0.634807065278803[/C][/ROW]
[ROW][C]9[/C][C]0.605282505694044[/C][/ROW]
[ROW][C]10[/C][C]0.579245810714212[/C][/ROW]
[ROW][C]11[/C][C]0.558519375427474[/C][/ROW]
[ROW][C]12[/C][C]0.535099457413163[/C][/ROW]
[ROW][C]13[/C][C]0.514681628604418[/C][/ROW]
[ROW][C]14[/C][C]0.480998917157005[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=4836&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=4836&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])
-14-0.209251261431644
-13-0.169704350499039
-12-0.131169674095478
-11-0.0948128396805245
-10-0.0558942546245996
-90.00111997796156646
-80.0472344178379564
-70.0854564679371574
-60.133414442029052
-50.191496288904784
-40.256510938769746
-30.308296435529034
-20.354487487730379
-10.393380105398595
00.420297325164524
10.459326336008560
20.504819796398376
30.549232577555124
40.59274471854401
50.632045401807002
60.677290319521592
70.660033965322932
80.634807065278803
90.605282505694044
100.579245810714212
110.558519375427474
120.535099457413163
130.514681628604418
140.480998917157005


Figures (Output of Computation)

Input Parameters & R Code

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',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')