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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationFri, 24 Dec 2010 15:25:06 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/24/t1293204189ppig6ps1gsal007.htm/, Retrieved Tue, 30 Apr 2024 03:22:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=115113, Retrieved Tue, 30 Apr 2024 03:22:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact128

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] [workshop 10] [2010-12-24 15:25:06] [fdda052f11cae2ac9ab9683c59d96811] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
9700
9081
9084
9743
8587
9731
9563
9998
9437
10038
9918
9252
9737
9035
9133
9487
8700
9627
8947
9283
8829
9947
9628
9318
9605
8640
9214
9567
8547
9185
9470
9123
9278
10170
9434
9655
9429
8739
9552
9687
9019
9672
9206
9069
9788
10312
10105
9863
9656
9295
9946
9701
9049
10190
9706
9765
9893
9994
10433
10073
10112
9266
9820
10097
9115
10411
9678
10408
10153
10368
10581
10597
10680
9738
9556
Dataseries Y:
Download CSV
Histogram 
235.1
280.7
264.6
240.7
201.4
240.8
241.1
223.8
206.1
174.7
203.3
220.5
299.5
347.4
338.3
327.7
351.6
396.6
438.8
395.6
363.5
378.8
357
369
464.8
479.1
431.3
366.5
326.3
355.1
331.6
261.3
249
205.5
235.6
240.9
264.9
253.8
232.3
193.8
177
213.2
207.2
180.6
188.6
175.4
199
179.6
225.8
234
200.2
183.6
178.2
203.2
208.5
191.8
172.8
148
159.4
154.5
213.2
196.4
182.8
176.4
153.6
173.2
171
151.2
161.9
157.2
201.7
236.4
356.1
398.3
403.7

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115113&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]2 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=115113&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115113&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 time2 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 series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-140.0477703863319752
-130.095463186139553
-120.242241358388638
-110.10959021314749
-100.237957191836880
-90.230855327705553
-80.175848005533646
-70.395972520751433
-60.260563717986979
-50.0990262309255264
-40.304051143622409
-30.272121692701369
-20.067231959325596
-10.317599032464795
00.118958735861893
10.204603648750494
20.261771601350106
3-0.119515630651513
40.0300801675963271
5-0.0957146125412563
6-0.0436950761873058
70.163565631858622
8-0.0256436950888604
9-0.177487928570599
100.0698589418108148
11-0.0803870992832234
12-0.0812372173963721
130.064085684336901
14-0.314095194663097

\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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-14 & 0.0477703863319752 \tabularnewline
-13 & 0.095463186139553 \tabularnewline
-12 & 0.242241358388638 \tabularnewline
-11 & 0.10959021314749 \tabularnewline
-10 & 0.237957191836880 \tabularnewline
-9 & 0.230855327705553 \tabularnewline
-8 & 0.175848005533646 \tabularnewline
-7 & 0.395972520751433 \tabularnewline
-6 & 0.260563717986979 \tabularnewline
-5 & 0.0990262309255264 \tabularnewline
-4 & 0.304051143622409 \tabularnewline
-3 & 0.272121692701369 \tabularnewline
-2 & 0.067231959325596 \tabularnewline
-1 & 0.317599032464795 \tabularnewline
0 & 0.118958735861893 \tabularnewline
1 & 0.204603648750494 \tabularnewline
2 & 0.261771601350106 \tabularnewline
3 & -0.119515630651513 \tabularnewline
4 & 0.0300801675963271 \tabularnewline
5 & -0.0957146125412563 \tabularnewline
6 & -0.0436950761873058 \tabularnewline
7 & 0.163565631858622 \tabularnewline
8 & -0.0256436950888604 \tabularnewline
9 & -0.177487928570599 \tabularnewline
10 & 0.0698589418108148 \tabularnewline
11 & -0.0803870992832234 \tabularnewline
12 & -0.0812372173963721 \tabularnewline
13 & 0.064085684336901 \tabularnewline
14 & -0.314095194663097 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=115113&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]1[/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]-14[/C][C]0.0477703863319752[/C][/ROW]
[ROW][C]-13[/C][C]0.095463186139553[/C][/ROW]
[ROW][C]-12[/C][C]0.242241358388638[/C][/ROW]
[ROW][C]-11[/C][C]0.10959021314749[/C][/ROW]
[ROW][C]-10[/C][C]0.237957191836880[/C][/ROW]
[ROW][C]-9[/C][C]0.230855327705553[/C][/ROW]
[ROW][C]-8[/C][C]0.175848005533646[/C][/ROW]
[ROW][C]-7[/C][C]0.395972520751433[/C][/ROW]
[ROW][C]-6[/C][C]0.260563717986979[/C][/ROW]
[ROW][C]-5[/C][C]0.0990262309255264[/C][/ROW]
[ROW][C]-4[/C][C]0.304051143622409[/C][/ROW]
[ROW][C]-3[/C][C]0.272121692701369[/C][/ROW]
[ROW][C]-2[/C][C]0.067231959325596[/C][/ROW]
[ROW][C]-1[/C][C]0.317599032464795[/C][/ROW]
[ROW][C]0[/C][C]0.118958735861893[/C][/ROW]
[ROW][C]1[/C][C]0.204603648750494[/C][/ROW]
[ROW][C]2[/C][C]0.261771601350106[/C][/ROW]
[ROW][C]3[/C][C]-0.119515630651513[/C][/ROW]
[ROW][C]4[/C][C]0.0300801675963271[/C][/ROW]
[ROW][C]5[/C][C]-0.0957146125412563[/C][/ROW]
[ROW][C]6[/C][C]-0.0436950761873058[/C][/ROW]
[ROW][C]7[/C][C]0.163565631858622[/C][/ROW]
[ROW][C]8[/C][C]-0.0256436950888604[/C][/ROW]
[ROW][C]9[/C][C]-0.177487928570599[/C][/ROW]
[ROW][C]10[/C][C]0.0698589418108148[/C][/ROW]
[ROW][C]11[/C][C]-0.0803870992832234[/C][/ROW]
[ROW][C]12[/C][C]-0.0812372173963721[/C][/ROW]
[ROW][C]13[/C][C]0.064085684336901[/C][/ROW]
[ROW][C]14[/C][C]-0.314095194663097[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=115113&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=115113&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 series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-140.0477703863319752
-130.095463186139553
-120.242241358388638
-110.10959021314749
-100.237957191836880
-90.230855327705553
-80.175848005533646
-70.395972520751433
-60.260563717986979
-50.0990262309255264
-40.304051143622409
-30.272121692701369
-20.067231959325596
-10.317599032464795
00.118958735861893
10.204603648750494
20.261771601350106
3-0.119515630651513
40.0300801675963271
5-0.0957146125412563
6-0.0436950761873058
70.163565631858622
8-0.0256436950888604
9-0.177487928570599
100.0698589418108148
11-0.0803870992832234
12-0.0812372173963721
130.064085684336901
14-0.314095194663097


Figures (Output of Computation)

Input Parameters & R Code

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