Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_cross.wasp

Title produced by software

Cross Correlation Function

Date of computation

Sun, 30 Nov 2008 15:15:34 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Nov/30/t1228083381kk5xzdbo4cf2982.htm/, Retrieved Mon, 20 May 2024 12:27:45 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=26767, Retrieved Mon, 20 May 2024 12:27:45 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

140

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

F     [Law of Averages] [Random Walk Simul...] [2008-11-25 18:40:39] [b98453cac15ba1066b407e146608df68]
F RMPD    [Cross Correlation Function] [Non Stationary Ti...] [2008-11-30 22:15:34] [7957bb37a64ed417bbed8444b0b0ea8a] [Current]

Feedback Forum

2008-12-08 18:57:09 [Stéphanie Claes] [reply] 
Hier moesten we inderdaad nog geen enkele transformatie uitvoeren. 
Als we naar de grafiek kijken dan weten we dat alles wat binnen het betrouwbaarheidsinterval valt gelijk is aan 0 en dus niet significant is. 
Hier zien we dat er toch heel wat coëfficiënten positief significant zijn. 
 
Het verleden van Xt is namelijk gecorreleerd met het heden Yt en omgekeerd = simultaan effect.

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

Dataseries Y:

Download CSV

Histogram

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 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=26767&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=26767&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26767&T=0

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Cross Correlation Function
Parameter	Value
Box-Cox transformation parameter (lambda) of X series	1
Degree of non-seasonal differencing (d) of X series	0
Degree of seasonal differencing (D) of X series	0
Seasonal Period (s)	1
Box-Cox transformation parameter (lambda) of Y series	1
Degree of non-seasonal differencing (d) of Y series	0
Degree of seasonal differencing (D) of Y series	0
k	rho(Y[t],X[t+k])
-16	0.195852662558113
-15	0.238263542218332
-14	0.245467410517630
-13	0.302422343010996
-12	0.281367192027717
-11	0.131011245168950
-10	0.116400360309794
-9	0.200253289374569
-8	0.0761979624679342
-7	0.133197290897126
-6	0.226871624344031
-5	0.158207597747634
-4	0.320449514309406
-3	0.325312590300533
-2	0.376111970860811
-1	0.478630839995608
0	0.329469746988351
1	0.203524490107066
2	0.162263644663247
3	0.127410426604194
4	0.0162963888073795
5	0.141742501112601
6	0.129987491332976
7	0.0795145641963642
8	0.198584423486323
9	0.226872885520388
10	0.191086792251095
11	0.26016544734164
12	0.172865632117652
13	0.116508123737878
14	0.0116822951201362
15	-0.00626159072869177
16	0.0132553212561324

\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
-16 & 0.195852662558113 \tabularnewline
-15 & 0.238263542218332 \tabularnewline
-14 & 0.245467410517630 \tabularnewline
-13 & 0.302422343010996 \tabularnewline
-12 & 0.281367192027717 \tabularnewline
-11 & 0.131011245168950 \tabularnewline
-10 & 0.116400360309794 \tabularnewline
-9 & 0.200253289374569 \tabularnewline
-8 & 0.0761979624679342 \tabularnewline
-7 & 0.133197290897126 \tabularnewline
-6 & 0.226871624344031 \tabularnewline
-5 & 0.158207597747634 \tabularnewline
-4 & 0.320449514309406 \tabularnewline
-3 & 0.325312590300533 \tabularnewline
-2 & 0.376111970860811 \tabularnewline
-1 & 0.478630839995608 \tabularnewline
0 & 0.329469746988351 \tabularnewline
1 & 0.203524490107066 \tabularnewline
2 & 0.162263644663247 \tabularnewline
3 & 0.127410426604194 \tabularnewline
4 & 0.0162963888073795 \tabularnewline
5 & 0.141742501112601 \tabularnewline
6 & 0.129987491332976 \tabularnewline
7 & 0.0795145641963642 \tabularnewline
8 & 0.198584423486323 \tabularnewline
9 & 0.226872885520388 \tabularnewline
10 & 0.191086792251095 \tabularnewline
11 & 0.26016544734164 \tabularnewline
12 & 0.172865632117652 \tabularnewline
13 & 0.116508123737878 \tabularnewline
14 & 0.0116822951201362 \tabularnewline
15 & -0.00626159072869177 \tabularnewline
16 & 0.0132553212561324 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=26767&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]-16[/C][C]0.195852662558113[/C][/ROW]
[ROW][C]-15[/C][C]0.238263542218332[/C][/ROW]
[ROW][C]-14[/C][C]0.245467410517630[/C][/ROW]
[ROW][C]-13[/C][C]0.302422343010996[/C][/ROW]
[ROW][C]-12[/C][C]0.281367192027717[/C][/ROW]
[ROW][C]-11[/C][C]0.131011245168950[/C][/ROW]
[ROW][C]-10[/C][C]0.116400360309794[/C][/ROW]
[ROW][C]-9[/C][C]0.200253289374569[/C][/ROW]
[ROW][C]-8[/C][C]0.0761979624679342[/C][/ROW]
[ROW][C]-7[/C][C]0.133197290897126[/C][/ROW]
[ROW][C]-6[/C][C]0.226871624344031[/C][/ROW]
[ROW][C]-5[/C][C]0.158207597747634[/C][/ROW]
[ROW][C]-4[/C][C]0.320449514309406[/C][/ROW]
[ROW][C]-3[/C][C]0.325312590300533[/C][/ROW]
[ROW][C]-2[/C][C]0.376111970860811[/C][/ROW]
[ROW][C]-1[/C][C]0.478630839995608[/C][/ROW]
[ROW][C]0[/C][C]0.329469746988351[/C][/ROW]
[ROW][C]1[/C][C]0.203524490107066[/C][/ROW]
[ROW][C]2[/C][C]0.162263644663247[/C][/ROW]
[ROW][C]3[/C][C]0.127410426604194[/C][/ROW]
[ROW][C]4[/C][C]0.0162963888073795[/C][/ROW]
[ROW][C]5[/C][C]0.141742501112601[/C][/ROW]
[ROW][C]6[/C][C]0.129987491332976[/C][/ROW]
[ROW][C]7[/C][C]0.0795145641963642[/C][/ROW]
[ROW][C]8[/C][C]0.198584423486323[/C][/ROW]
[ROW][C]9[/C][C]0.226872885520388[/C][/ROW]
[ROW][C]10[/C][C]0.191086792251095[/C][/ROW]
[ROW][C]11[/C][C]0.26016544734164[/C][/ROW]
[ROW][C]12[/C][C]0.172865632117652[/C][/ROW]
[ROW][C]13[/C][C]0.116508123737878[/C][/ROW]
[ROW][C]14[/C][C]0.0116822951201362[/C][/ROW]
[ROW][C]15[/C][C]-0.00626159072869177[/C][/ROW]
[ROW][C]16[/C][C]0.0132553212561324[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=26767&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=26767&T=1

As an alternative you can also use a QR Code:

The GUIDs for individual cells are displayed in the table below:

Cross Correlation Function
Parameter	Value
Box-Cox transformation parameter (lambda) of X series	1
Degree of non-seasonal differencing (d) of X series	0
Degree of seasonal differencing (D) of X series	0
Seasonal Period (s)	1
Box-Cox transformation parameter (lambda) of Y series	1
Degree of non-seasonal differencing (d) of Y series	0
Degree of seasonal differencing (D) of Y series	0
k	rho(Y[t],X[t+k])
-16	0.195852662558113
-15	0.238263542218332
-14	0.245467410517630
-13	0.302422343010996
-12	0.281367192027717
-11	0.131011245168950
-10	0.116400360309794
-9	0.200253289374569
-8	0.0761979624679342
-7	0.133197290897126
-6	0.226871624344031
-5	0.158207597747634
-4	0.320449514309406
-3	0.325312590300533
-2	0.376111970860811
-1	0.478630839995608
0	0.329469746988351
1	0.203524490107066
2	0.162263644663247
3	0.127410426604194
4	0.0162963888073795
5	0.141742501112601
6	0.129987491332976
7	0.0795145641963642
8	0.198584423486323
9	0.226872885520388
10	0.191086792251095
11	0.26016544734164
12	0.172865632117652
13	0.116508123737878
14	0.0116822951201362
15	-0.00626159072869177
16	0.0132553212561324

Figure 1

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = Default ; par2 = 1 ; par3 = 2 ; par4 = 2 ; par5 = 12 ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code