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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, 06 Jan 2008 14:23:49 -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/2008/Jan/06/t1199654587a01zx8jvwmh2hyz.htm/, Retrieved Sun, 05 May 2024 01:41:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=7903, Retrieved Sun, 05 May 2024 01:41:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsInducing time series Q5 WG-EA
Estimated Impact172

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Central Tendency] [WS2 - Robustness ...] [2007-10-20 13:06:37] [5343e105a400b9e32bf6f011133bbaf4]
- RM D    [Cross Correlation Function] [CVWS7Q5WG-EA] [2008-01-06 21:23:49] [b523c8d839cc24a05ea912c062a47207] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
59.9
59.9
59.9
60.9
60.9
60.9
61.1
61.1
61.1
60.2
60.2
60.2
60.1
60.1
60.1
59.7
59.7
59.7
60.5
60.5
60.5
59.5
59.5
59.5
59.5
59.5
59.5
59.7
59.7
59.7
60.4
60.4
60.4
60
60
60
59
59
59
59.3
59.3
59.3
59.7
59.7
59.7
60.4
60.4
60.4
59.9
59.9
59.9
60.5
60.5
60.5
60.4
60.4
60.4
60.6
60.6
60.6
60.9
60.9
60.9
61
61
61
61.2
61.2
61.2
61.2
61.2
61.2
60.3
60.3
60.3
60.4
60.4
60.4
61.2
61.2
61.2
62.1
62.1
62.1
61.7
61.7
61.7
61.6
61.6
61.6
Dataseries Y:
Download CSV
Histogram 
13,5
16,2
17,6
15,8
17,6
15,2
15,9
12,0
13,3
14,8
16,1
16,9
17,6
13,9
10,0
7,6
7,1
8,1
8,1
7,7
4,0
1,4
0,3
-1,0
-1,9
-1,5
-0,2
3,4
3,0
4,1
3,4
3,2
6,1
5,8
6,2
5,8
5,9
6,7
5,9
3,8
1,7
1,4
1,8
3,0
3,6
4,8
4,3
4,2
2,9
4,9
7,2
8,7
9,1
8,9
9,0
11,6
9,6
9,1
9,2
10,8
11,0
8,5
6,5
7,2
7,8
8,7
7,8
7,5
7,7
7,5
8,3
7,9
10,4
11,5
14,0
11,9
11,9
10,3
11,3
9,9
8,9
9,2
8,8
6,7
7,1
6,6
7,2
5,0
5,3
6,3

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7903&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7903&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7903&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'George Udny Yule' @ 72.249.76.132






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])
-160.051833596313958
-150.106581925476202
-140.153507467291796
-130.182507064408193
-120.197852120361277
-110.211155213659787
-100.237724236757925
-90.276845074756613
-80.314424753159148
-70.339313115145966
-60.344548370817211
-50.355476247841577
-40.345472254661322
-30.330897926126964
-20.301141920794985
-10.300090012941319
00.318837355847688
10.349876184636617
20.362281596756564
30.349912204075454
40.320331719697481
50.312978476736411
60.314244434533987
70.306922560961248
80.282139747739875
90.230692216333372
100.202169433919616
110.168564810596137
120.142938345354457
130.127365215495620
140.102319268463890
150.0621606572888673
160.0189798823368140

\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 & 0.051833596313958 \tabularnewline
-15 & 0.106581925476202 \tabularnewline
-14 & 0.153507467291796 \tabularnewline
-13 & 0.182507064408193 \tabularnewline
-12 & 0.197852120361277 \tabularnewline
-11 & 0.211155213659787 \tabularnewline
-10 & 0.237724236757925 \tabularnewline
-9 & 0.276845074756613 \tabularnewline
-8 & 0.314424753159148 \tabularnewline
-7 & 0.339313115145966 \tabularnewline
-6 & 0.344548370817211 \tabularnewline
-5 & 0.355476247841577 \tabularnewline
-4 & 0.345472254661322 \tabularnewline
-3 & 0.330897926126964 \tabularnewline
-2 & 0.301141920794985 \tabularnewline
-1 & 0.300090012941319 \tabularnewline
0 & 0.318837355847688 \tabularnewline
1 & 0.349876184636617 \tabularnewline
2 & 0.362281596756564 \tabularnewline
3 & 0.349912204075454 \tabularnewline
4 & 0.320331719697481 \tabularnewline
5 & 0.312978476736411 \tabularnewline
6 & 0.314244434533987 \tabularnewline
7 & 0.306922560961248 \tabularnewline
8 & 0.282139747739875 \tabularnewline
9 & 0.230692216333372 \tabularnewline
10 & 0.202169433919616 \tabularnewline
11 & 0.168564810596137 \tabularnewline
12 & 0.142938345354457 \tabularnewline
13 & 0.127365215495620 \tabularnewline
14 & 0.102319268463890 \tabularnewline
15 & 0.0621606572888673 \tabularnewline
16 & 0.0189798823368140 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=7903&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]0.051833596313958[/C][/ROW]
[ROW][C]-15[/C][C]0.106581925476202[/C][/ROW]
[ROW][C]-14[/C][C]0.153507467291796[/C][/ROW]
[ROW][C]-13[/C][C]0.182507064408193[/C][/ROW]
[ROW][C]-12[/C][C]0.197852120361277[/C][/ROW]
[ROW][C]-11[/C][C]0.211155213659787[/C][/ROW]
[ROW][C]-10[/C][C]0.237724236757925[/C][/ROW]
[ROW][C]-9[/C][C]0.276845074756613[/C][/ROW]
[ROW][C]-8[/C][C]0.314424753159148[/C][/ROW]
[ROW][C]-7[/C][C]0.339313115145966[/C][/ROW]
[ROW][C]-6[/C][C]0.344548370817211[/C][/ROW]
[ROW][C]-5[/C][C]0.355476247841577[/C][/ROW]
[ROW][C]-4[/C][C]0.345472254661322[/C][/ROW]
[ROW][C]-3[/C][C]0.330897926126964[/C][/ROW]
[ROW][C]-2[/C][C]0.301141920794985[/C][/ROW]
[ROW][C]-1[/C][C]0.300090012941319[/C][/ROW]
[ROW][C]0[/C][C]0.318837355847688[/C][/ROW]
[ROW][C]1[/C][C]0.349876184636617[/C][/ROW]
[ROW][C]2[/C][C]0.362281596756564[/C][/ROW]
[ROW][C]3[/C][C]0.349912204075454[/C][/ROW]
[ROW][C]4[/C][C]0.320331719697481[/C][/ROW]
[ROW][C]5[/C][C]0.312978476736411[/C][/ROW]
[ROW][C]6[/C][C]0.314244434533987[/C][/ROW]
[ROW][C]7[/C][C]0.306922560961248[/C][/ROW]
[ROW][C]8[/C][C]0.282139747739875[/C][/ROW]
[ROW][C]9[/C][C]0.230692216333372[/C][/ROW]
[ROW][C]10[/C][C]0.202169433919616[/C][/ROW]
[ROW][C]11[/C][C]0.168564810596137[/C][/ROW]
[ROW][C]12[/C][C]0.142938345354457[/C][/ROW]
[ROW][C]13[/C][C]0.127365215495620[/C][/ROW]
[ROW][C]14[/C][C]0.102319268463890[/C][/ROW]
[ROW][C]15[/C][C]0.0621606572888673[/C][/ROW]
[ROW][C]16[/C][C]0.0189798823368140[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=7903&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=7903&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])
-160.051833596313958
-150.106581925476202
-140.153507467291796
-130.182507064408193
-120.197852120361277
-110.211155213659787
-100.237724236757925
-90.276845074756613
-80.314424753159148
-70.339313115145966
-60.344548370817211
-50.355476247841577
-40.345472254661322
-30.330897926126964
-20.301141920794985
-10.300090012941319
00.318837355847688
10.349876184636617
20.362281596756564
30.349912204075454
40.320331719697481
50.312978476736411
60.314244434533987
70.306922560961248
80.282139747739875
90.230692216333372
100.202169433919616
110.168564810596137
120.142938345354457
130.127365215495620
140.102319268463890
150.0621606572888673
160.0189798823368140


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
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')