FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationSun, 19 Dec 2010 11:41:57 +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/19/t1292759292usd7jq1nujwcnio.htm/, Retrieved Sat, 04 May 2024 20:13:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=112302, Retrieved Sat, 04 May 2024 20:13:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact143

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] [appelen] [2009-12-17 16:17:08] [7773f496f69461f4a67891f0ef752622]
-   PD    [Cross Correlation Function] [CCKoffie] [2010-12-19 11:41:57] [9be3691a9b6ce074cb51fd18377fce28] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,64
1,65
1,65
1,65
1,66
1,66
1,67
1,67
1,68
1,68
1,68
1,68
1,69
1,69
1,7
1,7
1,71
1,71
1,71
1,71
1,72
1,72
1,72
1,73
1,73
1,73
1,74
1,75
1,75
1,76
1,76
1,77
1,77
1,78
1,79
1,8
1,8
1,81
1,81
1,81
1,81
1,82
1,82
1,82
1,83
1,83
1,83
1,84
1,84
1,85
1,85
1,86
1,86
1,86
1,86
1,86
Dataseries Y:
Download CSV
Histogram 
7,14
7,24
7,33
7,61
7,66
7,69
7,7
7,68
7,71
7,71
7,72
7,68
7,72
7,74
7,76
7,9
7,97
7,96
7,95
7,97
7,93
7,99
7,96
7,92
7,97
7,98
8
8,04
8,17
8,29
8,26
8,3
8,32
8,28
8,27
8,32
8,31
8,34
8,32
8,36
8,33
8,35
8,34
8,37
8,31
8,33
8,34
8,25
8,27
8,31
8,25
8,3
8,3
8,35
8,78
8,9

Tables (Output of Computation)





Summary of computational 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 computational 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=112302&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]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=112302&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112302&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 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])
-140.156359234820999
-130.204859103550727
-120.251622186823476
-110.305120707485673
-100.352804772487549
-90.397808146892784
-80.447055049118759
-70.494300872448649
-60.542090115451802
-50.58885994090412
-40.63930695109338
-30.689791717488226
-20.761495471422684
-10.833992105674459
00.911397046652479
10.838924684247152
20.77942562376853
30.749791721908827
40.72042211348823
50.695417392120614
60.668638129090433
70.639729685752357
80.611878416170702
90.588543058464376
100.555051281455281
110.518576764204853
120.480063411852754
130.439496391603933
140.396475217991989

\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 & 0.156359234820999 \tabularnewline
-13 & 0.204859103550727 \tabularnewline
-12 & 0.251622186823476 \tabularnewline
-11 & 0.305120707485673 \tabularnewline
-10 & 0.352804772487549 \tabularnewline
-9 & 0.397808146892784 \tabularnewline
-8 & 0.447055049118759 \tabularnewline
-7 & 0.494300872448649 \tabularnewline
-6 & 0.542090115451802 \tabularnewline
-5 & 0.58885994090412 \tabularnewline
-4 & 0.63930695109338 \tabularnewline
-3 & 0.689791717488226 \tabularnewline
-2 & 0.761495471422684 \tabularnewline
-1 & 0.833992105674459 \tabularnewline
0 & 0.911397046652479 \tabularnewline
1 & 0.838924684247152 \tabularnewline
2 & 0.77942562376853 \tabularnewline
3 & 0.749791721908827 \tabularnewline
4 & 0.72042211348823 \tabularnewline
5 & 0.695417392120614 \tabularnewline
6 & 0.668638129090433 \tabularnewline
7 & 0.639729685752357 \tabularnewline
8 & 0.611878416170702 \tabularnewline
9 & 0.588543058464376 \tabularnewline
10 & 0.555051281455281 \tabularnewline
11 & 0.518576764204853 \tabularnewline
12 & 0.480063411852754 \tabularnewline
13 & 0.439496391603933 \tabularnewline
14 & 0.396475217991989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=112302&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]0.156359234820999[/C][/ROW]
[ROW][C]-13[/C][C]0.204859103550727[/C][/ROW]
[ROW][C]-12[/C][C]0.251622186823476[/C][/ROW]
[ROW][C]-11[/C][C]0.305120707485673[/C][/ROW]
[ROW][C]-10[/C][C]0.352804772487549[/C][/ROW]
[ROW][C]-9[/C][C]0.397808146892784[/C][/ROW]
[ROW][C]-8[/C][C]0.447055049118759[/C][/ROW]
[ROW][C]-7[/C][C]0.494300872448649[/C][/ROW]
[ROW][C]-6[/C][C]0.542090115451802[/C][/ROW]
[ROW][C]-5[/C][C]0.58885994090412[/C][/ROW]
[ROW][C]-4[/C][C]0.63930695109338[/C][/ROW]
[ROW][C]-3[/C][C]0.689791717488226[/C][/ROW]
[ROW][C]-2[/C][C]0.761495471422684[/C][/ROW]
[ROW][C]-1[/C][C]0.833992105674459[/C][/ROW]
[ROW][C]0[/C][C]0.911397046652479[/C][/ROW]
[ROW][C]1[/C][C]0.838924684247152[/C][/ROW]
[ROW][C]2[/C][C]0.77942562376853[/C][/ROW]
[ROW][C]3[/C][C]0.749791721908827[/C][/ROW]
[ROW][C]4[/C][C]0.72042211348823[/C][/ROW]
[ROW][C]5[/C][C]0.695417392120614[/C][/ROW]
[ROW][C]6[/C][C]0.668638129090433[/C][/ROW]
[ROW][C]7[/C][C]0.639729685752357[/C][/ROW]
[ROW][C]8[/C][C]0.611878416170702[/C][/ROW]
[ROW][C]9[/C][C]0.588543058464376[/C][/ROW]
[ROW][C]10[/C][C]0.555051281455281[/C][/ROW]
[ROW][C]11[/C][C]0.518576764204853[/C][/ROW]
[ROW][C]12[/C][C]0.480063411852754[/C][/ROW]
[ROW][C]13[/C][C]0.439496391603933[/C][/ROW]
[ROW][C]14[/C][C]0.396475217991989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=112302&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=112302&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])
-140.156359234820999
-130.204859103550727
-120.251622186823476
-110.305120707485673
-100.352804772487549
-90.397808146892784
-80.447055049118759
-70.494300872448649
-60.542090115451802
-50.58885994090412
-40.63930695109338
-30.689791717488226
-20.761495471422684
-10.833992105674459
00.911397046652479
10.838924684247152
20.77942562376853
30.749791721908827
40.72042211348823
50.695417392120614
60.668638129090433
70.639729685752357
80.611878416170702
90.588543058464376
100.555051281455281
110.518576764204853
120.480063411852754
130.439496391603933
140.396475217991989


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) 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')