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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 computationSun, 21 Dec 2008 14:24:39 -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/21/t1229894733j000io3sq5l6s3g.htm/, Retrieved Sat, 18 May 2024 11:08:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35832, Retrieved Sat, 18 May 2024 11:08:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact165

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] [cross correlation...] [2008-12-19 12:35:03] [fad8a251ac01c156a8ae23a83577546f]
-   P     [Cross Correlation Function] [cross correlation...] [2008-12-21 21:24:39] [fa8b44cd657c07c6ee11bb2476ca3f8d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93,0
99,2
112,2
112,1
103,3
108,2
90,4
72,8
111,0
117,9
111,3
110,5
94,8
100,4
132,1
114,6
101,9
130,2
84,0
86,4
122,3
120,9
110,2
112,6
102,0
105,0
130,5
115,5
103,7
130,9
89,1
93,8
123,8
111,9
118,3
116,9
103,6
116,6
141,3
107,0
125,2
136,4
91,6
95,3
132,3
130,6
131,9
118,6
114,3
111,3
126,5
112,1
119,3
142,4
101,1
97,4
129,1
136,9
129,8
123,9
Dataseries Y:
Download CSV
Histogram 
72,5
72,0
98,8
75,2
81,2
88,0
54,6
68,6
101,5
93,4
84,5
91,4
64,5
64,5
117,3
73,5
79,7
102,6
57,9
73,1
102,4
82,3
89,1
84,7
81,4
67,5
113,9
83,8
73,9
103,9
67,9
62,5
125,4
79,1
106,3
96,2
94,3
85,6
117,4
88,5
124,2
119,3
76,8
70,6
122,1
109,5
119,9
102,3
79,6
78,2
103,6
77,8
99,1
105,7
84,1
88,7
108,0
98,1
101,0
82,0

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=35832&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=35832&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35832&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)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])
-14-0.162124925873775
-13-0.0901334495380728
-120.53833044458755
-110.077132640070228
-10-0.230738351757223
-90.195595774877151
-8-0.038889889584076
-7-0.00578034027655892
-60.513149735521828
-50.122738623570679
-4-0.161703533923639
-30.243620831920485
-2-0.150329027944329
-1-0.0286924466405646
00.827144070819714
10.187383875483870
2-0.184635837990393
30.279790317861983
4-0.0362625936714214
50.0358855068541595
60.593781029634755
70.0937593358201186
8-0.12133933469711
90.191025860643358
10-0.19477840676022
11-0.0368459812146714
120.684866352133106
130.0874963511978194
14-0.181045113700984

\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 & -0.162124925873775 \tabularnewline
-13 & -0.0901334495380728 \tabularnewline
-12 & 0.53833044458755 \tabularnewline
-11 & 0.077132640070228 \tabularnewline
-10 & -0.230738351757223 \tabularnewline
-9 & 0.195595774877151 \tabularnewline
-8 & -0.038889889584076 \tabularnewline
-7 & -0.00578034027655892 \tabularnewline
-6 & 0.513149735521828 \tabularnewline
-5 & 0.122738623570679 \tabularnewline
-4 & -0.161703533923639 \tabularnewline
-3 & 0.243620831920485 \tabularnewline
-2 & -0.150329027944329 \tabularnewline
-1 & -0.0286924466405646 \tabularnewline
0 & 0.827144070819714 \tabularnewline
1 & 0.187383875483870 \tabularnewline
2 & -0.184635837990393 \tabularnewline
3 & 0.279790317861983 \tabularnewline
4 & -0.0362625936714214 \tabularnewline
5 & 0.0358855068541595 \tabularnewline
6 & 0.593781029634755 \tabularnewline
7 & 0.0937593358201186 \tabularnewline
8 & -0.12133933469711 \tabularnewline
9 & 0.191025860643358 \tabularnewline
10 & -0.19477840676022 \tabularnewline
11 & -0.0368459812146714 \tabularnewline
12 & 0.684866352133106 \tabularnewline
13 & 0.0874963511978194 \tabularnewline
14 & -0.181045113700984 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35832&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]-0.162124925873775[/C][/ROW]
[ROW][C]-13[/C][C]-0.0901334495380728[/C][/ROW]
[ROW][C]-12[/C][C]0.53833044458755[/C][/ROW]
[ROW][C]-11[/C][C]0.077132640070228[/C][/ROW]
[ROW][C]-10[/C][C]-0.230738351757223[/C][/ROW]
[ROW][C]-9[/C][C]0.195595774877151[/C][/ROW]
[ROW][C]-8[/C][C]-0.038889889584076[/C][/ROW]
[ROW][C]-7[/C][C]-0.00578034027655892[/C][/ROW]
[ROW][C]-6[/C][C]0.513149735521828[/C][/ROW]
[ROW][C]-5[/C][C]0.122738623570679[/C][/ROW]
[ROW][C]-4[/C][C]-0.161703533923639[/C][/ROW]
[ROW][C]-3[/C][C]0.243620831920485[/C][/ROW]
[ROW][C]-2[/C][C]-0.150329027944329[/C][/ROW]
[ROW][C]-1[/C][C]-0.0286924466405646[/C][/ROW]
[ROW][C]0[/C][C]0.827144070819714[/C][/ROW]
[ROW][C]1[/C][C]0.187383875483870[/C][/ROW]
[ROW][C]2[/C][C]-0.184635837990393[/C][/ROW]
[ROW][C]3[/C][C]0.279790317861983[/C][/ROW]
[ROW][C]4[/C][C]-0.0362625936714214[/C][/ROW]
[ROW][C]5[/C][C]0.0358855068541595[/C][/ROW]
[ROW][C]6[/C][C]0.593781029634755[/C][/ROW]
[ROW][C]7[/C][C]0.0937593358201186[/C][/ROW]
[ROW][C]8[/C][C]-0.12133933469711[/C][/ROW]
[ROW][C]9[/C][C]0.191025860643358[/C][/ROW]
[ROW][C]10[/C][C]-0.19477840676022[/C][/ROW]
[ROW][C]11[/C][C]-0.0368459812146714[/C][/ROW]
[ROW][C]12[/C][C]0.684866352133106[/C][/ROW]
[ROW][C]13[/C][C]0.0874963511978194[/C][/ROW]
[ROW][C]14[/C][C]-0.181045113700984[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35832&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35832&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])
-14-0.162124925873775
-13-0.0901334495380728
-120.53833044458755
-110.077132640070228
-10-0.230738351757223
-90.195595774877151
-8-0.038889889584076
-7-0.00578034027655892
-60.513149735521828
-50.122738623570679
-4-0.161703533923639
-30.243620831920485
-2-0.150329027944329
-1-0.0286924466405646
00.827144070819714
10.187383875483870
2-0.184635837990393
30.279790317861983
4-0.0362625936714214
50.0358855068541595
60.593781029634755
70.0937593358201186
8-0.12133933469711
90.191025860643358
10-0.19477840676022
11-0.0368459812146714
120.684866352133106
130.0874963511978194
14-0.181045113700984


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')