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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 11:14:24 -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/t1229019543j03o6e458vw4ron.htm/, Retrieved Sat, 25 May 2024 12:23:08 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32420, Retrieved Sat, 25 May 2024 12:23:08 +0000
QR Codes:

Original text written by user:Total unemployment = x unemployment under 25 = y
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact199

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [Werkloosheid 50 e...] [2008-11-28 13:15:36] [6743688719638b0cb1c0a6e0bf433315]
-   P   [Univariate Data Series] [Unemployment from...] [2008-12-02 18:04:33] [6743688719638b0cb1c0a6e0bf433315]
- RMP     [Variance Reduction Matrix] [unemployment abov...] [2008-12-03 16:43:35] [6743688719638b0cb1c0a6e0bf433315]
- RMPD        [Cross Correlation Function] [CCF total and und...] [2008-12-11 18:14:24] [9b05d7ef5dbcfba4217d280d9092f628] [Current]
-    D          [Cross Correlation Function] [ccf total unemplo...] [2008-12-11 19:47:08] [6743688719638b0cb1c0a6e0bf433315]
-    D          [Cross Correlation Function] [CCF total unemplo...] [2008-12-11 19:52:15] [6743688719638b0cb1c0a6e0bf433315]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
569323
579714
577992
565464
547344
554788
562325
560854
555332
543599
536662
542722
593530
610763
612613
611324
594167
595454
590865
589379
584428
573100
567456
569028
620735
628884
628232
612117
595404
597141
593408
590072
579799
574205
572775
572942
619567
625809
619916
587625
565742
557274
560576
548854
531673
525919
511038
498662
555362
564591
541657
527070
509846
514258
516922
507561
492622
490243
469357
477580
528379
Dataseries Y:
Download CSV
Histogram 
150739
159129
157928
147768
137507
136919
136151
133001
125554
119647
114158
116193
152803
161761
160942
149470
139208
134588
130322
126611
122401
117352
112135
112879
148729
157230
157221
146681
136524
132111
125326
122716
116615
113719
110737
112093
143565
149946
149147
134339
122683
115614
116566
111272
104609
101802
94542
93051
124129
130374
123946
114971
105531
104919
104782
101281
94545
93248
84031
87486
115867

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=32420&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=32420&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32420&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 series1
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.080860480694483
-12-0.113664710044499
-110.164652260750993
-10-0.0770240844437678
-9-0.0230290348736806
-80.0324083483575516
-7-0.00717976582339247
-6-0.0102330482217050
-50.0108228864379786
-40.0635147407160336
-3-0.0972705388677566
-20.0192301660295513
-1-0.106330234814688
00.755755576926012
1-0.0604903154416588
20.137326163914963
30.0428349597859124
40.0659532961438352
5-0.272096912634289
60.145328947865650
70.0319441227393141
80.060195383008763
90.0580143354436328
100.0269137964282603
110.128169736476056
12-0.273819280099154
13-0.129558824605558

\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 & 1 \tabularnewline
Degree of seasonal differencing (D) of X series & 1 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-13 & -0.080860480694483 \tabularnewline
-12 & -0.113664710044499 \tabularnewline
-11 & 0.164652260750993 \tabularnewline
-10 & -0.0770240844437678 \tabularnewline
-9 & -0.0230290348736806 \tabularnewline
-8 & 0.0324083483575516 \tabularnewline
-7 & -0.00717976582339247 \tabularnewline
-6 & -0.0102330482217050 \tabularnewline
-5 & 0.0108228864379786 \tabularnewline
-4 & 0.0635147407160336 \tabularnewline
-3 & -0.0972705388677566 \tabularnewline
-2 & 0.0192301660295513 \tabularnewline
-1 & -0.106330234814688 \tabularnewline
0 & 0.755755576926012 \tabularnewline
1 & -0.0604903154416588 \tabularnewline
2 & 0.137326163914963 \tabularnewline
3 & 0.0428349597859124 \tabularnewline
4 & 0.0659532961438352 \tabularnewline
5 & -0.272096912634289 \tabularnewline
6 & 0.145328947865650 \tabularnewline
7 & 0.0319441227393141 \tabularnewline
8 & 0.060195383008763 \tabularnewline
9 & 0.0580143354436328 \tabularnewline
10 & 0.0269137964282603 \tabularnewline
11 & 0.128169736476056 \tabularnewline
12 & -0.273819280099154 \tabularnewline
13 & -0.129558824605558 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32420&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]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of X series[/C][C]1[/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]1[/C][/ROW]
[ROW][C]Degree of seasonal differencing (D) of Y series[/C][C]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-13[/C][C]-0.080860480694483[/C][/ROW]
[ROW][C]-12[/C][C]-0.113664710044499[/C][/ROW]
[ROW][C]-11[/C][C]0.164652260750993[/C][/ROW]
[ROW][C]-10[/C][C]-0.0770240844437678[/C][/ROW]
[ROW][C]-9[/C][C]-0.0230290348736806[/C][/ROW]
[ROW][C]-8[/C][C]0.0324083483575516[/C][/ROW]
[ROW][C]-7[/C][C]-0.00717976582339247[/C][/ROW]
[ROW][C]-6[/C][C]-0.0102330482217050[/C][/ROW]
[ROW][C]-5[/C][C]0.0108228864379786[/C][/ROW]
[ROW][C]-4[/C][C]0.0635147407160336[/C][/ROW]
[ROW][C]-3[/C][C]-0.0972705388677566[/C][/ROW]
[ROW][C]-2[/C][C]0.0192301660295513[/C][/ROW]
[ROW][C]-1[/C][C]-0.106330234814688[/C][/ROW]
[ROW][C]0[/C][C]0.755755576926012[/C][/ROW]
[ROW][C]1[/C][C]-0.0604903154416588[/C][/ROW]
[ROW][C]2[/C][C]0.137326163914963[/C][/ROW]
[ROW][C]3[/C][C]0.0428349597859124[/C][/ROW]
[ROW][C]4[/C][C]0.0659532961438352[/C][/ROW]
[ROW][C]5[/C][C]-0.272096912634289[/C][/ROW]
[ROW][C]6[/C][C]0.145328947865650[/C][/ROW]
[ROW][C]7[/C][C]0.0319441227393141[/C][/ROW]
[ROW][C]8[/C][C]0.060195383008763[/C][/ROW]
[ROW][C]9[/C][C]0.0580143354436328[/C][/ROW]
[ROW][C]10[/C][C]0.0269137964282603[/C][/ROW]
[ROW][C]11[/C][C]0.128169736476056[/C][/ROW]
[ROW][C]12[/C][C]-0.273819280099154[/C][/ROW]
[ROW][C]13[/C][C]-0.129558824605558[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32420&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32420&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 series1
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.080860480694483
-12-0.113664710044499
-110.164652260750993
-10-0.0770240844437678
-9-0.0230290348736806
-80.0324083483575516
-7-0.00717976582339247
-6-0.0102330482217050
-50.0108228864379786
-40.0635147407160336
-3-0.0972705388677566
-20.0192301660295513
-1-0.106330234814688
00.755755576926012
1-0.0604903154416588
20.137326163914963
30.0428349597859124
40.0659532961438352
5-0.272096912634289
60.145328947865650
70.0319441227393141
80.060195383008763
90.0580143354436328
100.0269137964282603
110.128169736476056
12-0.273819280099154
13-0.129558824605558


Figures (Output of Computation)

Input Parameters & R Code

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