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Description of Statistical Computation

Author's title

Author*Unverified author*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationSun, 25 Nov 2007 15:20:23 -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/2007/Nov/25/t119602866266x7kb9vb8dl6je.htm/, Retrieved Sat, 04 May 2024 08:51:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6565, Retrieved Sat, 04 May 2024 08:51:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsQ6
Estimated Impact172

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] [Inducing Stationa...] [2007-11-25 22:20:23] [c4516de5538230e4cf0ae0b9d9e43dd3] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
467.037
460.070
447.988
442.867
436.087
431.328
484.015
509.673
512.927
502.831
470.984
471.067
476.049
474.605
470.439
461.251
454.724
455.626
516.847
525.192
522.975
518.585
509.239
512.238
519.164
517.009
509.933
509.127
500.857
506.971
569.323
579.714
577.992
565.464
547.344
554.788
562.325
560.854
555.332
543.599
536.662
542.722
593.530
610.763
612.613
611.324
594.167
595.454
590.865
589.379
584.428
573.100
567.456
569.028
620.735
628.884
628.232
612.117
595.404
597.141
593.408
590.072
579.799
574.205
572.775
572.942
619.567
625.809
619.916
587.625
565.742
557.274
560.576
548.854
531.673
525.919
511.038
498.662
555.362
564.591
541.657
Dataseries Y:
Download CSV
Histogram 
90.8
96.4
90
92.1
97.2
95.1
88.5
91
90.5
75
66.3
66
68.4
70.6
83.9
90.1
90.6
87.1
90.8
94.1
99.8
96.8
87
96.3
107.1
115.2
106.1
89.5
91.3
97.6
100.7
104.6
94.7
101.8
102.5
105.3
110.3
109.8
117.3
118.8
131.3
125.9
133.1
147
145.8
164.4
149.8
137.7
151.7
156.8
180
180.4
170.4
191.6
199.5
218.2
217.5
205
194
199.3
219.3
211.1
215.2
240.2
242.2
240.7
255.4
253
218.2
203.7
205.6
215.6
188.5
202.9
214
230.3
230
241
259.6
247.8
270.3

Tables (Output of Computation)





Summary of compuational 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 compuational 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=6565&T=0

[TABLE]
[ROW][C]Summary of compuational 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=6565&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6565&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 compuational 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 series0
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 series0
krho(Y[t],X[t+k])
-16-0.170369965980607
-15-0.121917579937123
-14-0.164732389461811
-130.0351177664118349
-120.180749792069400
-110.0487743147987757
-100.0115658861165891
-9-0.0309226726601715
-80.0994498039919847
-70.0993665848779068
-60.0615019267286566
-5-0.0389069091529126
-4-0.279912275942231
-3-0.176217175214218
-2-0.161289499312606
-10.0378138511328938
00.167249482889661
10.178175798313562
2-0.00158452203355012
3-0.0299953510266668
40.121280375778779
50.124827447716585
60.0575924876687256
7-0.00701810518380582
8-0.131425462012411
9-0.191522202492745
10-0.237058676579561
110.099797298536819
120.185712545001434
130.00331274830174007
14-0.104178425601015
15-0.0328505019752700
160.0461877459362754

\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 & 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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & -0.170369965980607 \tabularnewline
-15 & -0.121917579937123 \tabularnewline
-14 & -0.164732389461811 \tabularnewline
-13 & 0.0351177664118349 \tabularnewline
-12 & 0.180749792069400 \tabularnewline
-11 & 0.0487743147987757 \tabularnewline
-10 & 0.0115658861165891 \tabularnewline
-9 & -0.0309226726601715 \tabularnewline
-8 & 0.0994498039919847 \tabularnewline
-7 & 0.0993665848779068 \tabularnewline
-6 & 0.0615019267286566 \tabularnewline
-5 & -0.0389069091529126 \tabularnewline
-4 & -0.279912275942231 \tabularnewline
-3 & -0.176217175214218 \tabularnewline
-2 & -0.161289499312606 \tabularnewline
-1 & 0.0378138511328938 \tabularnewline
0 & 0.167249482889661 \tabularnewline
1 & 0.178175798313562 \tabularnewline
2 & -0.00158452203355012 \tabularnewline
3 & -0.0299953510266668 \tabularnewline
4 & 0.121280375778779 \tabularnewline
5 & 0.124827447716585 \tabularnewline
6 & 0.0575924876687256 \tabularnewline
7 & -0.00701810518380582 \tabularnewline
8 & -0.131425462012411 \tabularnewline
9 & -0.191522202492745 \tabularnewline
10 & -0.237058676579561 \tabularnewline
11 & 0.099797298536819 \tabularnewline
12 & 0.185712545001434 \tabularnewline
13 & 0.00331274830174007 \tabularnewline
14 & -0.104178425601015 \tabularnewline
15 & -0.0328505019752700 \tabularnewline
16 & 0.0461877459362754 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6565&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]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]1[/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]-0.170369965980607[/C][/ROW]
[ROW][C]-15[/C][C]-0.121917579937123[/C][/ROW]
[ROW][C]-14[/C][C]-0.164732389461811[/C][/ROW]
[ROW][C]-13[/C][C]0.0351177664118349[/C][/ROW]
[ROW][C]-12[/C][C]0.180749792069400[/C][/ROW]
[ROW][C]-11[/C][C]0.0487743147987757[/C][/ROW]
[ROW][C]-10[/C][C]0.0115658861165891[/C][/ROW]
[ROW][C]-9[/C][C]-0.0309226726601715[/C][/ROW]
[ROW][C]-8[/C][C]0.0994498039919847[/C][/ROW]
[ROW][C]-7[/C][C]0.0993665848779068[/C][/ROW]
[ROW][C]-6[/C][C]0.0615019267286566[/C][/ROW]
[ROW][C]-5[/C][C]-0.0389069091529126[/C][/ROW]
[ROW][C]-4[/C][C]-0.279912275942231[/C][/ROW]
[ROW][C]-3[/C][C]-0.176217175214218[/C][/ROW]
[ROW][C]-2[/C][C]-0.161289499312606[/C][/ROW]
[ROW][C]-1[/C][C]0.0378138511328938[/C][/ROW]
[ROW][C]0[/C][C]0.167249482889661[/C][/ROW]
[ROW][C]1[/C][C]0.178175798313562[/C][/ROW]
[ROW][C]2[/C][C]-0.00158452203355012[/C][/ROW]
[ROW][C]3[/C][C]-0.0299953510266668[/C][/ROW]
[ROW][C]4[/C][C]0.121280375778779[/C][/ROW]
[ROW][C]5[/C][C]0.124827447716585[/C][/ROW]
[ROW][C]6[/C][C]0.0575924876687256[/C][/ROW]
[ROW][C]7[/C][C]-0.00701810518380582[/C][/ROW]
[ROW][C]8[/C][C]-0.131425462012411[/C][/ROW]
[ROW][C]9[/C][C]-0.191522202492745[/C][/ROW]
[ROW][C]10[/C][C]-0.237058676579561[/C][/ROW]
[ROW][C]11[/C][C]0.099797298536819[/C][/ROW]
[ROW][C]12[/C][C]0.185712545001434[/C][/ROW]
[ROW][C]13[/C][C]0.00331274830174007[/C][/ROW]
[ROW][C]14[/C][C]-0.104178425601015[/C][/ROW]
[ROW][C]15[/C][C]-0.0328505019752700[/C][/ROW]
[ROW][C]16[/C][C]0.0461877459362754[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6565&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6565&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 series0
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 series0
krho(Y[t],X[t+k])
-16-0.170369965980607
-15-0.121917579937123
-14-0.164732389461811
-130.0351177664118349
-120.180749792069400
-110.0487743147987757
-100.0115658861165891
-9-0.0309226726601715
-80.0994498039919847
-70.0993665848779068
-60.0615019267286566
-5-0.0389069091529126
-4-0.279912275942231
-3-0.176217175214218
-2-0.161289499312606
-10.0378138511328938
00.167249482889661
10.178175798313562
2-0.00158452203355012
3-0.0299953510266668
40.121280375778779
50.124827447716585
60.0575924876687256
7-0.00701810518380582
8-0.131425462012411
9-0.191522202492745
10-0.237058676579561
110.099797298536819
120.185712545001434
130.00331274830174007
14-0.104178425601015
15-0.0328505019752700
160.0461877459362754


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ; par2 = 1 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 1 ; 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) x <- diff(y,lag=par4,difference=par7)
x
y
bitmap(file='test1.png')
(r <- ccf(x,y,main='Cross Correlation Function',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')