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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 computationFri, 07 Dec 2007 06:44:33 -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/07/t1197034340pglspwq29gyvltq.htm/, Retrieved Mon, 29 Apr 2024 02:53:03 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2822, Retrieved Mon, 29 Apr 2024 02:53:03 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact163

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 Correlation...] [2007-12-07 13:44:33] [9bb499d88394279c02e6a8b8cf177cf7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.8833
0.87
0.8758
0.8858
0.917
0.9554
0.9922
0.9778
0.9808
0.9811
1.0014
1.0183
1.0622
1.0773
1.0807
1.0848
1.1582
1.1663
1.1372
1.1139
1.1222
1.1692
1.1702
1.2286
1.2613
1.2646
1.2262
1.1985
1.2007
1.2138
1.2266
1.2176
1.2218
1.249
1.2991
1.3408
1.3119
1.3014
1.3201
1.2938
1.2694
1.2165
1.2037
1.2292
1.2256
1.2015
1.1786
1.1856
1.2103
1.1938
1.202
1.2271
1.277
1.265
1.2684
1.2811
1.2727
1.2611
1.2881
1.3213
1.2999
1.3074
1.3242
1.3516
1.3511
1.3419
1.3716
1.3622
1.3896
1.4227
Dataseries Y:
Download CSV
Histogram 
9041.46
9476.91
9420.10
9690.65
10084.25
10344.12
10086.71
9959.87
10256.23
10172.04
10258.34
10703.35
11484.51
11568.05
10991.80
10545.34
11462.71
11462.40
11285.57
11552.26
12171.38
12174.88
12531.67
13099.33
13331.94
13021.59
13040.64
13030.09
12362.41
12602.89
12794.66
12874.90
13015.84
13495.45
14123.82
14246.00
13652.94
13616.55
13934.98
13773.79
13585.12
13810.92
13657.18
14075.57
14663.08
15107.66
15358.34
16375.51
17602.60
17824.63
17892.97
19639.74
21790.73
19187.52
20357.82
20291.34
19264.86
18858.49
20156.19
20222.50
20251.14
21373.38
21091.86
21856.72
21532.48
21085.27
21388.73
21363.38
22842.24
24231.43

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=2822&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=2822&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2822&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 series0
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-15-0.133506124724412
-140.126442367623492
-130.00144048204589592
-12-0.0828866407243665
-110.0125113711670703
-100.0391981973354380
-9-0.037168034693985
-8-0.0150135653397831
-7-0.0293432515339292
-6-0.0277366576689352
-5-0.242463010233879
-4-0.0483563186665932
-3-0.126155104721848
-2-0.220574934094295
-1-0.140663280798986
00.45919675973896
10.212344304962163
2-0.194273310277157
30.0066136223549969
40.229945680849712
50.12530744928605
6-0.282960469273741
7-0.0343609402934363
80.0383590511093204
9-0.0521308912801864
10-0.092897883388766
110.204779936487323
120.173423415006590
130.0221410574790119
140.0471356213668436
15-0.055643552762225

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 1 \tabularnewline
Degree of seasonal differencing (D) of X series & 0 \tabularnewline
Seasonal Period (s) & 12 \tabularnewline
Box-Cox transformation parameter (lambda) of Y series & 0 \tabularnewline
Degree of non-seasonal differencing (d) of Y series & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & -0.133506124724412 \tabularnewline
-14 & 0.126442367623492 \tabularnewline
-13 & 0.00144048204589592 \tabularnewline
-12 & -0.0828866407243665 \tabularnewline
-11 & 0.0125113711670703 \tabularnewline
-10 & 0.0391981973354380 \tabularnewline
-9 & -0.037168034693985 \tabularnewline
-8 & -0.0150135653397831 \tabularnewline
-7 & -0.0293432515339292 \tabularnewline
-6 & -0.0277366576689352 \tabularnewline
-5 & -0.242463010233879 \tabularnewline
-4 & -0.0483563186665932 \tabularnewline
-3 & -0.126155104721848 \tabularnewline
-2 & -0.220574934094295 \tabularnewline
-1 & -0.140663280798986 \tabularnewline
0 & 0.45919675973896 \tabularnewline
1 & 0.212344304962163 \tabularnewline
2 & -0.194273310277157 \tabularnewline
3 & 0.0066136223549969 \tabularnewline
4 & 0.229945680849712 \tabularnewline
5 & 0.12530744928605 \tabularnewline
6 & -0.282960469273741 \tabularnewline
7 & -0.0343609402934363 \tabularnewline
8 & 0.0383590511093204 \tabularnewline
9 & -0.0521308912801864 \tabularnewline
10 & -0.092897883388766 \tabularnewline
11 & 0.204779936487323 \tabularnewline
12 & 0.173423415006590 \tabularnewline
13 & 0.0221410574790119 \tabularnewline
14 & 0.0471356213668436 \tabularnewline
15 & -0.055643552762225 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2822&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]0[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]1[/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]0[/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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]-0.133506124724412[/C][/ROW]
[ROW][C]-14[/C][C]0.126442367623492[/C][/ROW]
[ROW][C]-13[/C][C]0.00144048204589592[/C][/ROW]
[ROW][C]-12[/C][C]-0.0828866407243665[/C][/ROW]
[ROW][C]-11[/C][C]0.0125113711670703[/C][/ROW]
[ROW][C]-10[/C][C]0.0391981973354380[/C][/ROW]
[ROW][C]-9[/C][C]-0.037168034693985[/C][/ROW]
[ROW][C]-8[/C][C]-0.0150135653397831[/C][/ROW]
[ROW][C]-7[/C][C]-0.0293432515339292[/C][/ROW]
[ROW][C]-6[/C][C]-0.0277366576689352[/C][/ROW]
[ROW][C]-5[/C][C]-0.242463010233879[/C][/ROW]
[ROW][C]-4[/C][C]-0.0483563186665932[/C][/ROW]
[ROW][C]-3[/C][C]-0.126155104721848[/C][/ROW]
[ROW][C]-2[/C][C]-0.220574934094295[/C][/ROW]
[ROW][C]-1[/C][C]-0.140663280798986[/C][/ROW]
[ROW][C]0[/C][C]0.45919675973896[/C][/ROW]
[ROW][C]1[/C][C]0.212344304962163[/C][/ROW]
[ROW][C]2[/C][C]-0.194273310277157[/C][/ROW]
[ROW][C]3[/C][C]0.0066136223549969[/C][/ROW]
[ROW][C]4[/C][C]0.229945680849712[/C][/ROW]
[ROW][C]5[/C][C]0.12530744928605[/C][/ROW]
[ROW][C]6[/C][C]-0.282960469273741[/C][/ROW]
[ROW][C]7[/C][C]-0.0343609402934363[/C][/ROW]
[ROW][C]8[/C][C]0.0383590511093204[/C][/ROW]
[ROW][C]9[/C][C]-0.0521308912801864[/C][/ROW]
[ROW][C]10[/C][C]-0.092897883388766[/C][/ROW]
[ROW][C]11[/C][C]0.204779936487323[/C][/ROW]
[ROW][C]12[/C][C]0.173423415006590[/C][/ROW]
[ROW][C]13[/C][C]0.0221410574790119[/C][/ROW]
[ROW][C]14[/C][C]0.0471356213668436[/C][/ROW]
[ROW][C]15[/C][C]-0.055643552762225[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2822&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2822&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 series0
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-15-0.133506124724412
-140.126442367623492
-130.00144048204589592
-12-0.0828866407243665
-110.0125113711670703
-100.0391981973354380
-9-0.037168034693985
-8-0.0150135653397831
-7-0.0293432515339292
-6-0.0277366576689352
-5-0.242463010233879
-4-0.0483563186665932
-3-0.126155104721848
-2-0.220574934094295
-1-0.140663280798986
00.45919675973896
10.212344304962163
2-0.194273310277157
30.0066136223549969
40.229945680849712
50.12530744928605
6-0.282960469273741
7-0.0343609402934363
80.0383590511093204
9-0.0521308912801864
10-0.092897883388766
110.204779936487323
120.173423415006590
130.0221410574790119
140.0471356213668436
15-0.055643552762225


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.0 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 0.0 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 0.0 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 0.0 ; par6 = 1 ; 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')