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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 computationThu, 11 Dec 2008 10:53:07 -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/11/t1229018026ebkwgvq0meur2c2.htm/, Retrieved Sun, 19 May 2024 06:05:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32399, Retrieved Sun, 19 May 2024 06:05:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact158

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] [2008-12-11 17:53:07] [a9e6d7cd6e144e8b311d9f96a24c5a25] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2648,9
2669,6
3042,3
2604,2
2732,1
2621,7
2483,7
2479,3
2684,6
2834,7
2566,1
2251,2
2350
2299,8
2542,8
2530,2
2508,1
2616,8
2534,1
2181,8
2578,9
2841,9
2529,9
2103,2
2326,2
2452,6
2782,1
2727,3
2648,2
2760,7
2613
2225,4
2713,9
2923,3
2707
2473,9
2521
2531,8
3068,8
2826,9
2674,2
2966,6
2798,8
2629,6
3124,6
3115,7
3083
2863,9
2728,7
2789,4
3225,7
3148,2
2836,5
3153,5
2656,9
2834,7
3172,5
2998,8
3103,1
2735,6
2818,1
2874,4
3438,5
2949,1
3306,8
3530
3003,8
3206,4
3514,6
3522,6
3525,5
2996,2
3231,1
3030
3541,7
3113,2
3390,8
3424,2
3079,8
3123,4
3317,1
3579,9
3317,9
2668,1
Dataseries Y:
Download CSV
Histogram 
99,5
93,5
104,6
95,3
102,8
103,3
100,2
107,9
107,5
119,8
112
102,1
105,3
101,3
108,4
107,4
109,1
109,5
111,4
110,1
117
129,6
113,5
113,3
110,1
107,4
110,1
112,5
106
117,6
117,8
113,5
121,2
130,4
115,2
117,9
110,7
107,6
124,3
115,1
112,5
127,9
117,4
119,3
130,4
126
125,4
130,5
115,9
108,7
124
119,4
118,6
131,3
111,1
124,8
132,3
126,7
131,7
130,9
122,1
113,2
133,6
119,2
129,4
131,4
117,1
130,5
132,3
140,8
137,5
128,6
126,7
120,8
139,3
128,6
131,3
136,3
128,8
133,2
136,3
151,1
145
134,4

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=32399&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=32399&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32399&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
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])
-160.180118728346106
-150.237043544718891
-140.32273109085096
-130.36533508217002
-120.496123649464992
-110.360974177671105
-100.240588366015566
-90.388410914276772
-80.380141164509266
-70.473366233905479
-60.552625353067236
-50.540289598557266
-40.463994214169271
-30.529367949934641
-20.555892365672558
-10.608825784221891
00.793346903644725
10.521534236756642
20.427089669547382
30.536660335606341
40.472409856456054
50.584032848510328
60.609219161220009
70.531242795677375
80.475816638643596
90.498509637794785
100.469632984086308
110.521098920310496
120.613906648059852
130.386335212502433
140.311912133926910
150.326631026696452
160.268250315308554

\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 & 0.180118728346106 \tabularnewline
-15 & 0.237043544718891 \tabularnewline
-14 & 0.32273109085096 \tabularnewline
-13 & 0.36533508217002 \tabularnewline
-12 & 0.496123649464992 \tabularnewline
-11 & 0.360974177671105 \tabularnewline
-10 & 0.240588366015566 \tabularnewline
-9 & 0.388410914276772 \tabularnewline
-8 & 0.380141164509266 \tabularnewline
-7 & 0.473366233905479 \tabularnewline
-6 & 0.552625353067236 \tabularnewline
-5 & 0.540289598557266 \tabularnewline
-4 & 0.463994214169271 \tabularnewline
-3 & 0.529367949934641 \tabularnewline
-2 & 0.555892365672558 \tabularnewline
-1 & 0.608825784221891 \tabularnewline
0 & 0.793346903644725 \tabularnewline
1 & 0.521534236756642 \tabularnewline
2 & 0.427089669547382 \tabularnewline
3 & 0.536660335606341 \tabularnewline
4 & 0.472409856456054 \tabularnewline
5 & 0.584032848510328 \tabularnewline
6 & 0.609219161220009 \tabularnewline
7 & 0.531242795677375 \tabularnewline
8 & 0.475816638643596 \tabularnewline
9 & 0.498509637794785 \tabularnewline
10 & 0.469632984086308 \tabularnewline
11 & 0.521098920310496 \tabularnewline
12 & 0.613906648059852 \tabularnewline
13 & 0.386335212502433 \tabularnewline
14 & 0.311912133926910 \tabularnewline
15 & 0.326631026696452 \tabularnewline
16 & 0.268250315308554 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32399&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]0.180118728346106[/C][/ROW]
[ROW][C]-15[/C][C]0.237043544718891[/C][/ROW]
[ROW][C]-14[/C][C]0.32273109085096[/C][/ROW]
[ROW][C]-13[/C][C]0.36533508217002[/C][/ROW]
[ROW][C]-12[/C][C]0.496123649464992[/C][/ROW]
[ROW][C]-11[/C][C]0.360974177671105[/C][/ROW]
[ROW][C]-10[/C][C]0.240588366015566[/C][/ROW]
[ROW][C]-9[/C][C]0.388410914276772[/C][/ROW]
[ROW][C]-8[/C][C]0.380141164509266[/C][/ROW]
[ROW][C]-7[/C][C]0.473366233905479[/C][/ROW]
[ROW][C]-6[/C][C]0.552625353067236[/C][/ROW]
[ROW][C]-5[/C][C]0.540289598557266[/C][/ROW]
[ROW][C]-4[/C][C]0.463994214169271[/C][/ROW]
[ROW][C]-3[/C][C]0.529367949934641[/C][/ROW]
[ROW][C]-2[/C][C]0.555892365672558[/C][/ROW]
[ROW][C]-1[/C][C]0.608825784221891[/C][/ROW]
[ROW][C]0[/C][C]0.793346903644725[/C][/ROW]
[ROW][C]1[/C][C]0.521534236756642[/C][/ROW]
[ROW][C]2[/C][C]0.427089669547382[/C][/ROW]
[ROW][C]3[/C][C]0.536660335606341[/C][/ROW]
[ROW][C]4[/C][C]0.472409856456054[/C][/ROW]
[ROW][C]5[/C][C]0.584032848510328[/C][/ROW]
[ROW][C]6[/C][C]0.609219161220009[/C][/ROW]
[ROW][C]7[/C][C]0.531242795677375[/C][/ROW]
[ROW][C]8[/C][C]0.475816638643596[/C][/ROW]
[ROW][C]9[/C][C]0.498509637794785[/C][/ROW]
[ROW][C]10[/C][C]0.469632984086308[/C][/ROW]
[ROW][C]11[/C][C]0.521098920310496[/C][/ROW]
[ROW][C]12[/C][C]0.613906648059852[/C][/ROW]
[ROW][C]13[/C][C]0.386335212502433[/C][/ROW]
[ROW][C]14[/C][C]0.311912133926910[/C][/ROW]
[ROW][C]15[/C][C]0.326631026696452[/C][/ROW]
[ROW][C]16[/C][C]0.268250315308554[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32399&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32399&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])
-160.180118728346106
-150.237043544718891
-140.32273109085096
-130.36533508217002
-120.496123649464992
-110.360974177671105
-100.240588366015566
-90.388410914276772
-80.380141164509266
-70.473366233905479
-60.552625353067236
-50.540289598557266
-40.463994214169271
-30.529367949934641
-20.555892365672558
-10.608825784221891
00.793346903644725
10.521534236756642
20.427089669547382
30.536660335606341
40.472409856456054
50.584032848510328
60.609219161220009
70.531242795677375
80.475816638643596
90.498509637794785
100.469632984086308
110.521098920310496
120.613906648059852
130.386335212502433
140.311912133926910
150.326631026696452
160.268250315308554


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')