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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 computationSat, 06 Dec 2008 09:38:31 -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/Dec/06/t122858154663vbd3o8wx2woxq.htm/, Retrieved Fri, 17 May 2024 05:45:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29746, Retrieved Fri, 17 May 2024 05:45:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact198

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
- RMPD  [Standard Deviation-Mean Plot] [Q5 Randow walk task] [2008-11-29 13:16:45] [6743688719638b0cb1c0a6e0bf433315]
F         [Standard Deviation-Mean Plot] [Q5 ] [2008-11-29 15:18:13] [de72ca3f4fcfd0997c84e1ac92aea119]
F    D      [Standard Deviation-Mean Plot] [Q8 Workshop 4] [2008-12-02 17:47:16] [de72ca3f4fcfd0997c84e1ac92aea119]
F RMPD        [Cross Correlation Function] [Q9 Workshop 4] [2008-12-02 18:02:55] [de72ca3f4fcfd0997c84e1ac92aea119]
-   P             [Cross Correlation Function] [] [2008-12-06 16:38:31] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.9059
0.8883
0.8924
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
1.4684
Dataseries Y:
Download CSV
Histogram 
109.86
108.68
113.38
117.12
116.23
114.75
115.81
115.86
117.80
117.11
116.31
118.38
121.57
121.65
124.20
126.12
128.60
128.16
130.12
135.83
138.05
134.99
132.38
128.94
128.12
127.84
132.43
134.13
134.78
133.13
129.08
134.48
132.86
134.08
134.54
134.51
135.97
136.09
139.14
135.63
136.55
138.83
138.84
135.37
132.22
134.75
135.98
136.06
138.05
139.59
140.58
139.81
140.77
140.96
143.59
142.70
145.11
146.70
148.53
148.99
149.65
151.11
154.82
156.56
157.60
155.24
160.68
163.22
164.55
166.76
159.05
159.82
164.95
162.89

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'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29746&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29746&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29746&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'George Udny Yule' @ 72.249.76.132






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series1.8
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 series-0.2
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-15-0.20958223222925
-14-0.0276005637440242
-13-0.0617674828018615
-120.0970736871861365
-110.0735655388166051
-10-0.0193342339315764
-9-0.0777018944686201
-8-0.0377627826416198
-70.112124258876828
-6-0.196526602474302
-50.00827226463937157
-4-0.06855924734345
-30.0185885339255718
-2-0.0766657036194107
-10.0658433705317572
00.408710377233876
10.0978982695508128
2-0.233467767546972
3-0.225060803272546
4-0.0268764760963393
50.256240470572316
60.115875043435299
70.135463404348465
8-0.00253370928561441
90.0340968232083558
100.0469766340842605
11-0.0655871184983821
120.123463637833208
130.0663091650304041
14-0.106587303471131
15-0.0420670085865955

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 1.8 \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 & -0.2 \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 & -0.20958223222925 \tabularnewline
-14 & -0.0276005637440242 \tabularnewline
-13 & -0.0617674828018615 \tabularnewline
-12 & 0.0970736871861365 \tabularnewline
-11 & 0.0735655388166051 \tabularnewline
-10 & -0.0193342339315764 \tabularnewline
-9 & -0.0777018944686201 \tabularnewline
-8 & -0.0377627826416198 \tabularnewline
-7 & 0.112124258876828 \tabularnewline
-6 & -0.196526602474302 \tabularnewline
-5 & 0.00827226463937157 \tabularnewline
-4 & -0.06855924734345 \tabularnewline
-3 & 0.0185885339255718 \tabularnewline
-2 & -0.0766657036194107 \tabularnewline
-1 & 0.0658433705317572 \tabularnewline
0 & 0.408710377233876 \tabularnewline
1 & 0.0978982695508128 \tabularnewline
2 & -0.233467767546972 \tabularnewline
3 & -0.225060803272546 \tabularnewline
4 & -0.0268764760963393 \tabularnewline
5 & 0.256240470572316 \tabularnewline
6 & 0.115875043435299 \tabularnewline
7 & 0.135463404348465 \tabularnewline
8 & -0.00253370928561441 \tabularnewline
9 & 0.0340968232083558 \tabularnewline
10 & 0.0469766340842605 \tabularnewline
11 & -0.0655871184983821 \tabularnewline
12 & 0.123463637833208 \tabularnewline
13 & 0.0663091650304041 \tabularnewline
14 & -0.106587303471131 \tabularnewline
15 & -0.0420670085865955 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29746&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]1.8[/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]-0.2[/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]-0.20958223222925[/C][/ROW]
[ROW][C]-14[/C][C]-0.0276005637440242[/C][/ROW]
[ROW][C]-13[/C][C]-0.0617674828018615[/C][/ROW]
[ROW][C]-12[/C][C]0.0970736871861365[/C][/ROW]
[ROW][C]-11[/C][C]0.0735655388166051[/C][/ROW]
[ROW][C]-10[/C][C]-0.0193342339315764[/C][/ROW]
[ROW][C]-9[/C][C]-0.0777018944686201[/C][/ROW]
[ROW][C]-8[/C][C]-0.0377627826416198[/C][/ROW]
[ROW][C]-7[/C][C]0.112124258876828[/C][/ROW]
[ROW][C]-6[/C][C]-0.196526602474302[/C][/ROW]
[ROW][C]-5[/C][C]0.00827226463937157[/C][/ROW]
[ROW][C]-4[/C][C]-0.06855924734345[/C][/ROW]
[ROW][C]-3[/C][C]0.0185885339255718[/C][/ROW]
[ROW][C]-2[/C][C]-0.0766657036194107[/C][/ROW]
[ROW][C]-1[/C][C]0.0658433705317572[/C][/ROW]
[ROW][C]0[/C][C]0.408710377233876[/C][/ROW]
[ROW][C]1[/C][C]0.0978982695508128[/C][/ROW]
[ROW][C]2[/C][C]-0.233467767546972[/C][/ROW]
[ROW][C]3[/C][C]-0.225060803272546[/C][/ROW]
[ROW][C]4[/C][C]-0.0268764760963393[/C][/ROW]
[ROW][C]5[/C][C]0.256240470572316[/C][/ROW]
[ROW][C]6[/C][C]0.115875043435299[/C][/ROW]
[ROW][C]7[/C][C]0.135463404348465[/C][/ROW]
[ROW][C]8[/C][C]-0.00253370928561441[/C][/ROW]
[ROW][C]9[/C][C]0.0340968232083558[/C][/ROW]
[ROW][C]10[/C][C]0.0469766340842605[/C][/ROW]
[ROW][C]11[/C][C]-0.0655871184983821[/C][/ROW]
[ROW][C]12[/C][C]0.123463637833208[/C][/ROW]
[ROW][C]13[/C][C]0.0663091650304041[/C][/ROW]
[ROW][C]14[/C][C]-0.106587303471131[/C][/ROW]
[ROW][C]15[/C][C]-0.0420670085865955[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29746&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29746&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 series1.8
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 series-0.2
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-15-0.20958223222925
-14-0.0276005637440242
-13-0.0617674828018615
-120.0970736871861365
-110.0735655388166051
-10-0.0193342339315764
-9-0.0777018944686201
-8-0.0377627826416198
-70.112124258876828
-6-0.196526602474302
-50.00827226463937157
-4-0.06855924734345
-30.0185885339255718
-2-0.0766657036194107
-10.0658433705317572
00.408710377233876
10.0978982695508128
2-0.233467767546972
3-0.225060803272546
4-0.0268764760963393
50.256240470572316
60.115875043435299
70.135463404348465
8-0.00253370928561441
90.0340968232083558
100.0469766340842605
11-0.0655871184983821
120.123463637833208
130.0663091650304041
14-0.106587303471131
15-0.0420670085865955


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1.8 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = -0.2 ; par6 = 1 ; par7 = 0 ;
Parameters (R input):
par1 = 1.8 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = -0.2 ; 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) 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')