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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 computationTue, 02 Dec 2008 05:43:43 -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/t1228221864l9lessvjrljhk7b.htm/, Retrieved Sun, 19 May 2024 00:53:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=27695, Retrieved Sun, 19 May 2024 00:53:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact157

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Cross Correlation Function] [question 7] [2008-12-02 12:43:43] [490fee4f334e2e025c95681783e3fd0b] [Current]
Feedback Forum
2008-12-08 15:59:10 [Alexander Hendrickx] [reply] 
In deze grafiek is er kruiscorrelatie aanwezig de x loopt achter op de y en voorspelt deze

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,3322
1,4369
1,4975
1,577
1,5553
1,5557
1,575
1,5527
1,4748
1,4718
1,457
1,4684
1,4227
1,3896
1,3622
1,3716
1,3419
1,3511
1,3516
1,3242
1,3074
1,2999
1,3213
1,2881
1,2611
1,2727
1,2811
1,2684
1,265
1,277
1,2271
1,202
1,1938
1,2103
1,1856
1,1786
1,2015
1,2256
1,2292
1,2037
1,2165
1,2694
1,2938
1,3201
1,3014
1,3119
1,3408
1,2991
1,249
1,2218
1,2176
1,2266
1,2138
1,2007
1,1985
1,2262
1,2646
1,2613
1,2286
1,1702
1,1692
1,1222
1,1139
1,1372
1,1663
1,1582
1,0848
1,0807
1,0773
1,0622
1,0183
1,0014
0,9811
0,9808
Dataseries Y:
Download CSV
Histogram 
133,52
153,2
163,63
168,45
166,26
162,31
161,56
156,59
157,97
158,68
163,55
162,89
164,95
159,82
159,05
166,76
164,55
163,22
160,68
155,24
157,6
156,56
154,82
151,11
149,65
148,99
148,53
146,7
145,11
142,7
143,59
140,96
140,77
139,81
140,58
139,59
138,05
136,06
135,98
134,75
132,22
135,37
138,84
138,83
136,55
135,63
139,14
136,09
135,97
134,51
134,54
134,08
132,86
134,48
129,08
133,13
134,78
134,13
132,43
127,84
128,12
128,94
132,38
134,99
138,05
135,83
130,12
128,16
128,6
126,12
124,2
121,65
121,57
118,38

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 2 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27695&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27695&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27695&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 time2 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24






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)2
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])
-150.327288773097091
-140.375761299950727
-130.418164229796042
-120.468278696464702
-110.515461976221233
-100.558964589439761
-90.591238449516658
-80.612060078201164
-70.641655306128352
-60.669081334035189
-50.69458396792468
-40.715612906164804
-30.749811012297347
-20.792364287743534
-10.840993187684483
00.865800162602291
10.803699010028114
20.733002007353024
30.656770286893231
40.590450406601075
50.527873772563556
60.468729998421953
70.424658288749825
80.388053800663062
90.358191561005539
100.335777974256538
110.309439480526508
120.285641837990927
130.251828722203456
140.218501837413571
150.180499766727547

\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) & 2 \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 & 0.327288773097091 \tabularnewline
-14 & 0.375761299950727 \tabularnewline
-13 & 0.418164229796042 \tabularnewline
-12 & 0.468278696464702 \tabularnewline
-11 & 0.515461976221233 \tabularnewline
-10 & 0.558964589439761 \tabularnewline
-9 & 0.591238449516658 \tabularnewline
-8 & 0.612060078201164 \tabularnewline
-7 & 0.641655306128352 \tabularnewline
-6 & 0.669081334035189 \tabularnewline
-5 & 0.69458396792468 \tabularnewline
-4 & 0.715612906164804 \tabularnewline
-3 & 0.749811012297347 \tabularnewline
-2 & 0.792364287743534 \tabularnewline
-1 & 0.840993187684483 \tabularnewline
0 & 0.865800162602291 \tabularnewline
1 & 0.803699010028114 \tabularnewline
2 & 0.733002007353024 \tabularnewline
3 & 0.656770286893231 \tabularnewline
4 & 0.590450406601075 \tabularnewline
5 & 0.527873772563556 \tabularnewline
6 & 0.468729998421953 \tabularnewline
7 & 0.424658288749825 \tabularnewline
8 & 0.388053800663062 \tabularnewline
9 & 0.358191561005539 \tabularnewline
10 & 0.335777974256538 \tabularnewline
11 & 0.309439480526508 \tabularnewline
12 & 0.285641837990927 \tabularnewline
13 & 0.251828722203456 \tabularnewline
14 & 0.218501837413571 \tabularnewline
15 & 0.180499766727547 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=27695&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]2[/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]0.327288773097091[/C][/ROW]
[ROW][C]-14[/C][C]0.375761299950727[/C][/ROW]
[ROW][C]-13[/C][C]0.418164229796042[/C][/ROW]
[ROW][C]-12[/C][C]0.468278696464702[/C][/ROW]
[ROW][C]-11[/C][C]0.515461976221233[/C][/ROW]
[ROW][C]-10[/C][C]0.558964589439761[/C][/ROW]
[ROW][C]-9[/C][C]0.591238449516658[/C][/ROW]
[ROW][C]-8[/C][C]0.612060078201164[/C][/ROW]
[ROW][C]-7[/C][C]0.641655306128352[/C][/ROW]
[ROW][C]-6[/C][C]0.669081334035189[/C][/ROW]
[ROW][C]-5[/C][C]0.69458396792468[/C][/ROW]
[ROW][C]-4[/C][C]0.715612906164804[/C][/ROW]
[ROW][C]-3[/C][C]0.749811012297347[/C][/ROW]
[ROW][C]-2[/C][C]0.792364287743534[/C][/ROW]
[ROW][C]-1[/C][C]0.840993187684483[/C][/ROW]
[ROW][C]0[/C][C]0.865800162602291[/C][/ROW]
[ROW][C]1[/C][C]0.803699010028114[/C][/ROW]
[ROW][C]2[/C][C]0.733002007353024[/C][/ROW]
[ROW][C]3[/C][C]0.656770286893231[/C][/ROW]
[ROW][C]4[/C][C]0.590450406601075[/C][/ROW]
[ROW][C]5[/C][C]0.527873772563556[/C][/ROW]
[ROW][C]6[/C][C]0.468729998421953[/C][/ROW]
[ROW][C]7[/C][C]0.424658288749825[/C][/ROW]
[ROW][C]8[/C][C]0.388053800663062[/C][/ROW]
[ROW][C]9[/C][C]0.358191561005539[/C][/ROW]
[ROW][C]10[/C][C]0.335777974256538[/C][/ROW]
[ROW][C]11[/C][C]0.309439480526508[/C][/ROW]
[ROW][C]12[/C][C]0.285641837990927[/C][/ROW]
[ROW][C]13[/C][C]0.251828722203456[/C][/ROW]
[ROW][C]14[/C][C]0.218501837413571[/C][/ROW]
[ROW][C]15[/C][C]0.180499766727547[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=27695&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=27695&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)2
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])
-150.327288773097091
-140.375761299950727
-130.418164229796042
-120.468278696464702
-110.515461976221233
-100.558964589439761
-90.591238449516658
-80.612060078201164
-70.641655306128352
-60.669081334035189
-50.69458396792468
-40.715612906164804
-30.749811012297347
-20.792364287743534
-10.840993187684483
00.865800162602291
10.803699010028114
20.733002007353024
30.656770286893231
40.590450406601075
50.527873772563556
60.468729998421953
70.424658288749825
80.388053800663062
90.358191561005539
100.335777974256538
110.309439480526508
120.285641837990927
130.251828722203456
140.218501837413571
150.180499766727547


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 2 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 2 ; 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')