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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 12:52:15 -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/t1229025177g9mu7yqidyv2zgz.htm/, Retrieved Sat, 25 May 2024 03:34:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32441, Retrieved Sat, 25 May 2024 03:34:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact192

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] [6743688719638b0cb1c0a6e0bf433315]
-    D          [Cross Correlation Function] [CCF total unemplo...] [2008-12-11 19:52:15] [9b05d7ef5dbcfba4217d280d9092f628] [Current]
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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 
44028
45564
44277
44976
45406
47379
49200
50221
51573
53091
53337
54978
57885
67099
67169
69796
70600
71982
73957
75273
76322
77078
77954
79238
82179
83834
83744
84861
86478
88290
90287
91230
92380
92506
94172
94728
96581
97344
98346
98214
98366
98768
99832
99976
99961
100164
99964
99304
104008
104644
103950
104263
104241
105141
106018
105866
105944
106379
105082
104915
107026

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=32441&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=32441&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32441&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 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])
-130.00354622490723999
-12-0.158029644683787
-11-0.055492130427271
-10-0.102394510737764
-9-0.105359864736981
-80.0796577061874822
-70.00724821895244672
-60.0361185764812586
-5-0.0323102111020881
-40.0124675841359680
-30.0489921125511631
-20.0394404980017336
-1-0.0759553260184185
00.506463193392785
10.0491505312253793
20.223496997322999
30.0684534997520683
40.0161166075468359
5-0.134029141114457
60.0692034200414075
70.0160334207370995
8-0.0359718295008940
9-0.151079747275599
10-0.071376418314656
110.0921855283241258
12-0.272737700616078
13-0.070665039093225

\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 & 0.00354622490723999 \tabularnewline
-12 & -0.158029644683787 \tabularnewline
-11 & -0.055492130427271 \tabularnewline
-10 & -0.102394510737764 \tabularnewline
-9 & -0.105359864736981 \tabularnewline
-8 & 0.0796577061874822 \tabularnewline
-7 & 0.00724821895244672 \tabularnewline
-6 & 0.0361185764812586 \tabularnewline
-5 & -0.0323102111020881 \tabularnewline
-4 & 0.0124675841359680 \tabularnewline
-3 & 0.0489921125511631 \tabularnewline
-2 & 0.0394404980017336 \tabularnewline
-1 & -0.0759553260184185 \tabularnewline
0 & 0.506463193392785 \tabularnewline
1 & 0.0491505312253793 \tabularnewline
2 & 0.223496997322999 \tabularnewline
3 & 0.0684534997520683 \tabularnewline
4 & 0.0161166075468359 \tabularnewline
5 & -0.134029141114457 \tabularnewline
6 & 0.0692034200414075 \tabularnewline
7 & 0.0160334207370995 \tabularnewline
8 & -0.0359718295008940 \tabularnewline
9 & -0.151079747275599 \tabularnewline
10 & -0.071376418314656 \tabularnewline
11 & 0.0921855283241258 \tabularnewline
12 & -0.272737700616078 \tabularnewline
13 & -0.070665039093225 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32441&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]0.00354622490723999[/C][/ROW]
[ROW][C]-12[/C][C]-0.158029644683787[/C][/ROW]
[ROW][C]-11[/C][C]-0.055492130427271[/C][/ROW]
[ROW][C]-10[/C][C]-0.102394510737764[/C][/ROW]
[ROW][C]-9[/C][C]-0.105359864736981[/C][/ROW]
[ROW][C]-8[/C][C]0.0796577061874822[/C][/ROW]
[ROW][C]-7[/C][C]0.00724821895244672[/C][/ROW]
[ROW][C]-6[/C][C]0.0361185764812586[/C][/ROW]
[ROW][C]-5[/C][C]-0.0323102111020881[/C][/ROW]
[ROW][C]-4[/C][C]0.0124675841359680[/C][/ROW]
[ROW][C]-3[/C][C]0.0489921125511631[/C][/ROW]
[ROW][C]-2[/C][C]0.0394404980017336[/C][/ROW]
[ROW][C]-1[/C][C]-0.0759553260184185[/C][/ROW]
[ROW][C]0[/C][C]0.506463193392785[/C][/ROW]
[ROW][C]1[/C][C]0.0491505312253793[/C][/ROW]
[ROW][C]2[/C][C]0.223496997322999[/C][/ROW]
[ROW][C]3[/C][C]0.0684534997520683[/C][/ROW]
[ROW][C]4[/C][C]0.0161166075468359[/C][/ROW]
[ROW][C]5[/C][C]-0.134029141114457[/C][/ROW]
[ROW][C]6[/C][C]0.0692034200414075[/C][/ROW]
[ROW][C]7[/C][C]0.0160334207370995[/C][/ROW]
[ROW][C]8[/C][C]-0.0359718295008940[/C][/ROW]
[ROW][C]9[/C][C]-0.151079747275599[/C][/ROW]
[ROW][C]10[/C][C]-0.071376418314656[/C][/ROW]
[ROW][C]11[/C][C]0.0921855283241258[/C][/ROW]
[ROW][C]12[/C][C]-0.272737700616078[/C][/ROW]
[ROW][C]13[/C][C]-0.070665039093225[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32441&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32441&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])
-130.00354622490723999
-12-0.158029644683787
-11-0.055492130427271
-10-0.102394510737764
-9-0.105359864736981
-80.0796577061874822
-70.00724821895244672
-60.0361185764812586
-5-0.0323102111020881
-40.0124675841359680
-30.0489921125511631
-20.0394404980017336
-1-0.0759553260184185
00.506463193392785
10.0491505312253793
20.223496997322999
30.0684534997520683
40.0161166075468359
5-0.134029141114457
60.0692034200414075
70.0160334207370995
8-0.0359718295008940
9-0.151079747275599
10-0.071376418314656
110.0921855283241258
12-0.272737700616078
13-0.070665039093225


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')