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Description of Statistical Computation

Author's title

Crosscorrelatie: Industr. prod. van bouwnijverheid en bouwvergunningen: pap...

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationMon, 08 Dec 2008 07:17:20 -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/08/t1228745924pg9ksx9ra4u0ves.htm/, Retrieved Thu, 16 May 2024 10:15:32 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=30511, Retrieved Thu, 16 May 2024 10:15:32 +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] [Crosscorrelatie: ...] [2008-12-08 14:17:20] [b5110a3ab194da7214bdf478e0a05dbd] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
109.1
113.8
97.4
72.5
82.7
88.9
105.9
100.8
94
105
58.5
87.6
113.1
112.5
89.6
74.5
82.7
90.1
109.4
96
89.2
109.1
49.1
92.9
107.7
103.5
91.1
79.8
71.9
82.9
90.1
100.7
90.7
108.8
44.1
93.6
107.4
96.5
93.6
76.5
76.7
84
103.3
88.5
99
105.9
44.7
94
107.1
104.8
102.5
77.7
85.2
91.3
106.5
92.4
97.5
107
51.1
98.6
102.2
114.3
99.4
72.5
92.3
99.4
85.9
109.4
97.6
104.7
Dataseries Y:
Download CSV
Histogram 
2187
1852
1570
1851
1954
1828
2251
2277
2085
2282
2266
1878
2267
2069
1746
2299
2360
2214
2825
2355
2333
3016
2155
2172
2150
2533
2058
2160
2259
2498
2695
2799
2945
2930
2318
2540
2570
2669
2450
2842
3439
2677
2979
2257
2842
2546
2455
2293
2379
2478
2054
2272
2351
2271
2542
2304
2194
2722
2395
2146
1894
2548
2087
2063
2481
2476
2212
2834
2148
2598

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=30511&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=30511&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30511&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 series0
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)1
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])
-15-0.107001291419817
-14-0.0686809183515562
-13-0.0333851178954048
-120.0225071381965161
-11-0.185112608228614
-10-0.104621970049804
-90.0406014086933512
-8-0.0611955680211656
-70.0234681468402117
-6-0.165600382627192
-5-0.112694354568968
-40.0528174846821347
-3-0.193218304270885
-2-0.127092623300908
-1-0.153145208278122
00.116181889215923
1-0.189534243307357
2-0.0477672447117508
30.112846411564435
4-0.145225577175690
50.0205075696957065
6-0.0979873980523806
7-0.138094407878535
80.139501886548631
9-0.0912029561987063
10-0.0600491193345492
11-0.0444623644226560
120.115229523724794
13-0.0428149140423621
140.00398097734657685
150.133119742790953

\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) & 1 \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
-15 & -0.107001291419817 \tabularnewline
-14 & -0.0686809183515562 \tabularnewline
-13 & -0.0333851178954048 \tabularnewline
-12 & 0.0225071381965161 \tabularnewline
-11 & -0.185112608228614 \tabularnewline
-10 & -0.104621970049804 \tabularnewline
-9 & 0.0406014086933512 \tabularnewline
-8 & -0.0611955680211656 \tabularnewline
-7 & 0.0234681468402117 \tabularnewline
-6 & -0.165600382627192 \tabularnewline
-5 & -0.112694354568968 \tabularnewline
-4 & 0.0528174846821347 \tabularnewline
-3 & -0.193218304270885 \tabularnewline
-2 & -0.127092623300908 \tabularnewline
-1 & -0.153145208278122 \tabularnewline
0 & 0.116181889215923 \tabularnewline
1 & -0.189534243307357 \tabularnewline
2 & -0.0477672447117508 \tabularnewline
3 & 0.112846411564435 \tabularnewline
4 & -0.145225577175690 \tabularnewline
5 & 0.0205075696957065 \tabularnewline
6 & -0.0979873980523806 \tabularnewline
7 & -0.138094407878535 \tabularnewline
8 & 0.139501886548631 \tabularnewline
9 & -0.0912029561987063 \tabularnewline
10 & -0.0600491193345492 \tabularnewline
11 & -0.0444623644226560 \tabularnewline
12 & 0.115229523724794 \tabularnewline
13 & -0.0428149140423621 \tabularnewline
14 & 0.00398097734657685 \tabularnewline
15 & 0.133119742790953 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=30511&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]1[/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]-15[/C][C]-0.107001291419817[/C][/ROW]
[ROW][C]-14[/C][C]-0.0686809183515562[/C][/ROW]
[ROW][C]-13[/C][C]-0.0333851178954048[/C][/ROW]
[ROW][C]-12[/C][C]0.0225071381965161[/C][/ROW]
[ROW][C]-11[/C][C]-0.185112608228614[/C][/ROW]
[ROW][C]-10[/C][C]-0.104621970049804[/C][/ROW]
[ROW][C]-9[/C][C]0.0406014086933512[/C][/ROW]
[ROW][C]-8[/C][C]-0.0611955680211656[/C][/ROW]
[ROW][C]-7[/C][C]0.0234681468402117[/C][/ROW]
[ROW][C]-6[/C][C]-0.165600382627192[/C][/ROW]
[ROW][C]-5[/C][C]-0.112694354568968[/C][/ROW]
[ROW][C]-4[/C][C]0.0528174846821347[/C][/ROW]
[ROW][C]-3[/C][C]-0.193218304270885[/C][/ROW]
[ROW][C]-2[/C][C]-0.127092623300908[/C][/ROW]
[ROW][C]-1[/C][C]-0.153145208278122[/C][/ROW]
[ROW][C]0[/C][C]0.116181889215923[/C][/ROW]
[ROW][C]1[/C][C]-0.189534243307357[/C][/ROW]
[ROW][C]2[/C][C]-0.0477672447117508[/C][/ROW]
[ROW][C]3[/C][C]0.112846411564435[/C][/ROW]
[ROW][C]4[/C][C]-0.145225577175690[/C][/ROW]
[ROW][C]5[/C][C]0.0205075696957065[/C][/ROW]
[ROW][C]6[/C][C]-0.0979873980523806[/C][/ROW]
[ROW][C]7[/C][C]-0.138094407878535[/C][/ROW]
[ROW][C]8[/C][C]0.139501886548631[/C][/ROW]
[ROW][C]9[/C][C]-0.0912029561987063[/C][/ROW]
[ROW][C]10[/C][C]-0.0600491193345492[/C][/ROW]
[ROW][C]11[/C][C]-0.0444623644226560[/C][/ROW]
[ROW][C]12[/C][C]0.115229523724794[/C][/ROW]
[ROW][C]13[/C][C]-0.0428149140423621[/C][/ROW]
[ROW][C]14[/C][C]0.00398097734657685[/C][/ROW]
[ROW][C]15[/C][C]0.133119742790953[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=30511&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=30511&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)1
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])
-15-0.107001291419817
-14-0.0686809183515562
-13-0.0333851178954048
-120.0225071381965161
-11-0.185112608228614
-10-0.104621970049804
-90.0406014086933512
-8-0.0611955680211656
-70.0234681468402117
-6-0.165600382627192
-5-0.112694354568968
-40.0528174846821347
-3-0.193218304270885
-2-0.127092623300908
-1-0.153145208278122
00.116181889215923
1-0.189534243307357
2-0.0477672447117508
30.112846411564435
4-0.145225577175690
50.0205075696957065
6-0.0979873980523806
7-0.138094407878535
80.139501886548631
9-0.0912029561987063
10-0.0600491193345492
11-0.0444623644226560
120.115229523724794
13-0.0428149140423621
140.00398097734657685
150.133119742790953


Figures (Output of Computation)

Input Parameters & R Code

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