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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 computationMon, 01 Dec 2008 15:37:05 -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/01/t1228171064d73kc8ton3nz7f8.htm/, Retrieved Sun, 05 May 2024 09:54:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27473, Retrieved Sun, 05 May 2024 09:54:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsNon Stationary Time Series
Estimated Impact197

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Cross Correlation Function] [] [2008-11-26 19:16:07] [425b18c1b1aaa428d3e290037692d12d]
F         [Cross Correlation Function] [question 7: Cross...] [2008-12-01 22:37:05] [3efbb18563b4564408d69b3c9a8e9a6e] [Current]
Feedback Forum
2008-12-09 07:44:30 [An De Koninck] [reply] 
We zien duidelijk één significante observatie in het midden van de grafiek. Is er dus seizonaliteit in de reeks?

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
3353
3480
3098
2944
3389
3497
4404
3849
3734
3060
3507
3287
3215
3764
2734
2837
2766
3851
3289
3848
3348
3682
4058
3655
3811
3341
3032
3475
3353
3186
3902
4164
3499
4145
3796
3711
3949
3740
3243
4407
4814
3908
5250
3937
4004
5560
3922
3759
4138
4634
3996
4308
4142
4429
5219
4929
5754
5592
4163
4962
5208
4755
4491
5732
5730
5024
6056
4901
5353
5578
4618
4724
5011
5298
4143
4617
4727
4207
5112
4190
4098
5071
4177
4598
3757
5591
4218
3780
4336
4870
4422
4727
4459
Dataseries Y:
Download CSV
Histogram 
2341
2540
2371
2122
2301
2512
3145
2741
2548
1987
2281
2016
2434
2637
1831
1851
1839
2609
2417
2394
2372
2717
2998
2538
3007
2475
2175
2465
2279
2323
2746
2601
2486
2718
2646
2551
2712
2606
2365
3533
3509
2912
3599
2719
2869
4085
2686
2545
3071
3388
2652
3190
2884
3295
3818
3226
3953
3810
2877
3515
3708
3450
3360
4110
4384
3729
4263
3505
3674
3911
2951
3317
3417
3498
2768
2899
3171
3004
3481
3016
2595
3509
2833
3125
2556
3628
2876
2575
2903
3438
2926
3068
3015

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'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27473&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27473&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27473&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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])
-160.195227242304181
-150.306310634990256
-140.317089546338286
-130.290336291205997
-120.456690821885486
-110.384933896662601
-100.392135506809595
-90.518475402003846
-80.446387924580636
-70.461340796675185
-60.501507349281824
-50.504080564606302
-40.506844771316556
-30.627061664784509
-20.548685938015044
-10.580652558523755
00.963581341676323
10.618073896426325
20.590771006483437
30.648050367527059
40.561730021238873
50.526620563128284
60.548196482673601
70.513268922569985
80.436677449147771
90.554422211158063
100.473499151921076
110.433705573757664
120.546692235842891
130.372837797033769
140.384451064913571
150.417184996426881
160.312521877180668

\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 & 0.195227242304181 \tabularnewline
-15 & 0.306310634990256 \tabularnewline
-14 & 0.317089546338286 \tabularnewline
-13 & 0.290336291205997 \tabularnewline
-12 & 0.456690821885486 \tabularnewline
-11 & 0.384933896662601 \tabularnewline
-10 & 0.392135506809595 \tabularnewline
-9 & 0.518475402003846 \tabularnewline
-8 & 0.446387924580636 \tabularnewline
-7 & 0.461340796675185 \tabularnewline
-6 & 0.501507349281824 \tabularnewline
-5 & 0.504080564606302 \tabularnewline
-4 & 0.506844771316556 \tabularnewline
-3 & 0.627061664784509 \tabularnewline
-2 & 0.548685938015044 \tabularnewline
-1 & 0.580652558523755 \tabularnewline
0 & 0.963581341676323 \tabularnewline
1 & 0.618073896426325 \tabularnewline
2 & 0.590771006483437 \tabularnewline
3 & 0.648050367527059 \tabularnewline
4 & 0.561730021238873 \tabularnewline
5 & 0.526620563128284 \tabularnewline
6 & 0.548196482673601 \tabularnewline
7 & 0.513268922569985 \tabularnewline
8 & 0.436677449147771 \tabularnewline
9 & 0.554422211158063 \tabularnewline
10 & 0.473499151921076 \tabularnewline
11 & 0.433705573757664 \tabularnewline
12 & 0.546692235842891 \tabularnewline
13 & 0.372837797033769 \tabularnewline
14 & 0.384451064913571 \tabularnewline
15 & 0.417184996426881 \tabularnewline
16 & 0.312521877180668 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27473&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]0.195227242304181[/C][/ROW]
[ROW][C]-15[/C][C]0.306310634990256[/C][/ROW]
[ROW][C]-14[/C][C]0.317089546338286[/C][/ROW]
[ROW][C]-13[/C][C]0.290336291205997[/C][/ROW]
[ROW][C]-12[/C][C]0.456690821885486[/C][/ROW]
[ROW][C]-11[/C][C]0.384933896662601[/C][/ROW]
[ROW][C]-10[/C][C]0.392135506809595[/C][/ROW]
[ROW][C]-9[/C][C]0.518475402003846[/C][/ROW]
[ROW][C]-8[/C][C]0.446387924580636[/C][/ROW]
[ROW][C]-7[/C][C]0.461340796675185[/C][/ROW]
[ROW][C]-6[/C][C]0.501507349281824[/C][/ROW]
[ROW][C]-5[/C][C]0.504080564606302[/C][/ROW]
[ROW][C]-4[/C][C]0.506844771316556[/C][/ROW]
[ROW][C]-3[/C][C]0.627061664784509[/C][/ROW]
[ROW][C]-2[/C][C]0.548685938015044[/C][/ROW]
[ROW][C]-1[/C][C]0.580652558523755[/C][/ROW]
[ROW][C]0[/C][C]0.963581341676323[/C][/ROW]
[ROW][C]1[/C][C]0.618073896426325[/C][/ROW]
[ROW][C]2[/C][C]0.590771006483437[/C][/ROW]
[ROW][C]3[/C][C]0.648050367527059[/C][/ROW]
[ROW][C]4[/C][C]0.561730021238873[/C][/ROW]
[ROW][C]5[/C][C]0.526620563128284[/C][/ROW]
[ROW][C]6[/C][C]0.548196482673601[/C][/ROW]
[ROW][C]7[/C][C]0.513268922569985[/C][/ROW]
[ROW][C]8[/C][C]0.436677449147771[/C][/ROW]
[ROW][C]9[/C][C]0.554422211158063[/C][/ROW]
[ROW][C]10[/C][C]0.473499151921076[/C][/ROW]
[ROW][C]11[/C][C]0.433705573757664[/C][/ROW]
[ROW][C]12[/C][C]0.546692235842891[/C][/ROW]
[ROW][C]13[/C][C]0.372837797033769[/C][/ROW]
[ROW][C]14[/C][C]0.384451064913571[/C][/ROW]
[ROW][C]15[/C][C]0.417184996426881[/C][/ROW]
[ROW][C]16[/C][C]0.312521877180668[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27473&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27473&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])
-160.195227242304181
-150.306310634990256
-140.317089546338286
-130.290336291205997
-120.456690821885486
-110.384933896662601
-100.392135506809595
-90.518475402003846
-80.446387924580636
-70.461340796675185
-60.501507349281824
-50.504080564606302
-40.506844771316556
-30.627061664784509
-20.548685938015044
-10.580652558523755
00.963581341676323
10.618073896426325
20.590771006483437
30.648050367527059
40.561730021238873
50.526620563128284
60.548196482673601
70.513268922569985
80.436677449147771
90.554422211158063
100.473499151921076
110.433705573757664
120.546692235842891
130.372837797033769
140.384451064913571
150.417184996426881
160.312521877180668


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')