FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationTue, 02 Dec 2008 11:09:48 -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/02/t1228241929bv5483ra8ddz2v6.htm/, Retrieved Fri, 17 May 2024 05:14:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28202, Retrieved Fri, 17 May 2024 05:14:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact167

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Data Series] [Airline data] [2007-10-18 09:58:47] [42daae401fd3def69a25014f2252b4c2]
F RMPD    [Cross Correlation Function] [loïqueverhasselt] [2008-12-02 18:09:48] [6440ec5a21e5d35520cb2ae6b4b70e45] [Current]
F   PD      [Cross Correlation Function] [loïqueverhasselt] [2008-12-02 18:24:22] [0e879b146665902680dd148a904a2646]
F   P         [Cross Correlation Function] [loïqueverhasselt] [2008-12-02 19:32:23] [0e879b146665902680dd148a904a2646]
F RMPD        [Variance Reduction Matrix] [loïqueverhasselt] [2008-12-02 19:35:00] [0e879b146665902680dd148a904a2646]
F    D          [Variance Reduction Matrix] [loïqueverhasselt] [2008-12-02 19:39:59] [0e879b146665902680dd148a904a2646]
F RMPD          [Cross Correlation Function] [loïqueverhasselt] [2008-12-02 19:48:19] [0e879b146665902680dd148a904a2646]
Feedback Forum
2008-12-06 12:19:14 [Loïque Verhasselt] [reply] 
Q7: Correcte uitvoering van de voorgaande berekeningen op mijn eigen tijdreeks. We vinden duidelijk een cross correlatie functie die nog gezuiverd moet worden op stationair te maken. Dit doen we in Q8.
2008-12-07 09:23:04 [Gert-Jan Geudens] [reply] 
Correcte berekening. We kunnen hier afleiden dat we yt kunnen verklaren op basis van het verleden én de toekomst van xt.
2008-12-07 12:58:59 [Gert-Jan Geudens] [reply] 
Het kan uiteraard wel zijn dat we hier te maken hebben met een nonsenscorrelatie. Dit zullen we onderzoeken in Q9

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99,4
97,5
94,6
92,6
92,5
89,8
88,8
87,4
85,2
83,1
84,7
84,8
85,8
86,3
89
89
89,3
91,9
94,9
94,4
96,8
96,9
98
97,9
100,9
103,9
103,1
102,5
104,3
102,6
101,7
102,8
105,4
110,9
113,5
116,3
124
128,8
133,5
132,6
128,4
127,3
126,7
123,3
123,2
124,4
128,2
128,7
135,7
139
145,4
142,4
137,7
137
137,1
139,3
139,6
140,4
142,3
148,3
Dataseries Y:
Download CSV
Histogram 
93
98.4
92.6
94.6
99.5
97.6
91.3
93.6
93.1
78.4
70.2
69.3
71.1
73.5
85.9
91.5
91.8
88.3
91.3
94
99.3
96.7
88
96.7
106.8
114.3
105.7
90.1
91.6
97.7
100.8
104.6
95.9
102.7
104
107.9
113.8
113.8
123.1
125.1
137.6
134
140.3
152.1
150.6
167.3
153.2
142
154.4
158.5
180.9
181.3
172.4
192
199.3
215.4
214.3
201.5
190.5
196

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28202&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]0 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=28202&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28202&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 time0 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)12
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])
-140.434598513183933
-130.466981256764928
-120.500516024589581
-110.542958559132658
-100.590819811817221
-90.651269716074375
-80.703955556333435
-70.750228563213412
-60.788943799898969
-50.818164895482828
-40.840570180853678
-30.857346083238946
-20.872162339271406
-10.886691816443575
00.908206036957268
10.856697488864814
20.810523409522733
30.756509421047398
40.689898438792986
50.621202959758297
60.556466436829148
70.493172515810373
80.444286564394025
90.384280513782574
100.322637170707914
110.275581313245977
120.231506567401823
130.197141074382126
140.149975727183669

\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) & 12 \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
-14 & 0.434598513183933 \tabularnewline
-13 & 0.466981256764928 \tabularnewline
-12 & 0.500516024589581 \tabularnewline
-11 & 0.542958559132658 \tabularnewline
-10 & 0.590819811817221 \tabularnewline
-9 & 0.651269716074375 \tabularnewline
-8 & 0.703955556333435 \tabularnewline
-7 & 0.750228563213412 \tabularnewline
-6 & 0.788943799898969 \tabularnewline
-5 & 0.818164895482828 \tabularnewline
-4 & 0.840570180853678 \tabularnewline
-3 & 0.857346083238946 \tabularnewline
-2 & 0.872162339271406 \tabularnewline
-1 & 0.886691816443575 \tabularnewline
0 & 0.908206036957268 \tabularnewline
1 & 0.856697488864814 \tabularnewline
2 & 0.810523409522733 \tabularnewline
3 & 0.756509421047398 \tabularnewline
4 & 0.689898438792986 \tabularnewline
5 & 0.621202959758297 \tabularnewline
6 & 0.556466436829148 \tabularnewline
7 & 0.493172515810373 \tabularnewline
8 & 0.444286564394025 \tabularnewline
9 & 0.384280513782574 \tabularnewline
10 & 0.322637170707914 \tabularnewline
11 & 0.275581313245977 \tabularnewline
12 & 0.231506567401823 \tabularnewline
13 & 0.197141074382126 \tabularnewline
14 & 0.149975727183669 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28202&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]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]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]-14[/C][C]0.434598513183933[/C][/ROW]
[ROW][C]-13[/C][C]0.466981256764928[/C][/ROW]
[ROW][C]-12[/C][C]0.500516024589581[/C][/ROW]
[ROW][C]-11[/C][C]0.542958559132658[/C][/ROW]
[ROW][C]-10[/C][C]0.590819811817221[/C][/ROW]
[ROW][C]-9[/C][C]0.651269716074375[/C][/ROW]
[ROW][C]-8[/C][C]0.703955556333435[/C][/ROW]
[ROW][C]-7[/C][C]0.750228563213412[/C][/ROW]
[ROW][C]-6[/C][C]0.788943799898969[/C][/ROW]
[ROW][C]-5[/C][C]0.818164895482828[/C][/ROW]
[ROW][C]-4[/C][C]0.840570180853678[/C][/ROW]
[ROW][C]-3[/C][C]0.857346083238946[/C][/ROW]
[ROW][C]-2[/C][C]0.872162339271406[/C][/ROW]
[ROW][C]-1[/C][C]0.886691816443575[/C][/ROW]
[ROW][C]0[/C][C]0.908206036957268[/C][/ROW]
[ROW][C]1[/C][C]0.856697488864814[/C][/ROW]
[ROW][C]2[/C][C]0.810523409522733[/C][/ROW]
[ROW][C]3[/C][C]0.756509421047398[/C][/ROW]
[ROW][C]4[/C][C]0.689898438792986[/C][/ROW]
[ROW][C]5[/C][C]0.621202959758297[/C][/ROW]
[ROW][C]6[/C][C]0.556466436829148[/C][/ROW]
[ROW][C]7[/C][C]0.493172515810373[/C][/ROW]
[ROW][C]8[/C][C]0.444286564394025[/C][/ROW]
[ROW][C]9[/C][C]0.384280513782574[/C][/ROW]
[ROW][C]10[/C][C]0.322637170707914[/C][/ROW]
[ROW][C]11[/C][C]0.275581313245977[/C][/ROW]
[ROW][C]12[/C][C]0.231506567401823[/C][/ROW]
[ROW][C]13[/C][C]0.197141074382126[/C][/ROW]
[ROW][C]14[/C][C]0.149975727183669[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28202&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28202&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)12
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])
-140.434598513183933
-130.466981256764928
-120.500516024589581
-110.542958559132658
-100.590819811817221
-90.651269716074375
-80.703955556333435
-70.750228563213412
-60.788943799898969
-50.818164895482828
-40.840570180853678
-30.857346083238946
-20.872162339271406
-10.886691816443575
00.908206036957268
10.856697488864814
20.810523409522733
30.756509421047398
40.689898438792986
50.621202959758297
60.556466436829148
70.493172515810373
80.444286564394025
90.384280513782574
100.322637170707914
110.275581313245977
120.231506567401823
130.197141074382126
140.149975727183669


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; 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')