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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 computationFri, 23 Nov 2007 08:36:51 -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/23/t1195832614q9pet9h0iw63su2.htm/, Retrieved Sun, 28 Apr 2024 20:22:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6204, Retrieved Sun, 28 Apr 2024 20:22:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170

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] [] [2007-11-23 15:36:51] [2467046df5c61f7ccf2ce4e184abae94] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
92,4
92
95,6
95,8
96,4
99
107
109,7
116,2
115,9
113,8
112,6
113,7
115,9
110,3
111,3
113,4
108,2
104,8
106
110,9
115
118,4
121,4
128,8
131,7
141,7
142,9
139,4
134,7
125
113,6
111,5
108,5
112,3
116,6
115,5
120,1
132,9
128,1
129,3
132,5
131
124,9
120,8
122
122,1
127,4
135,2
137,3
135
136
138,4
134,7
138,4
133,9
133,6
141,2
151,8
155,4
Dataseries Y:
Download CSV
Histogram 
99,7
99
98,1
97
98,5
103,8
114,4
124,5
134,2
131,8
125,6
119,9
114,9
115,5
112,5
111,4
115,3
110,8
103,7
111,1
113
111,2
117,6
121,7
127,3
129,8
137,1
141,4
137,4
130,7
117,2
110,8
111,4
108,2
108,8
110,2
109,5
109,5
116
111,2
112,1
114
119,1
114,1
115,1
115,4
110,8
116
119,2
126,5
127,8
131,3
140,3
137,3
143
134,5
139,9
159,3
170,4
175

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6204&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6204&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6204&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 time2 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






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])
-140.0581787837405573
-13-0.00900806387794153
-120.0504019422117691
-110.087582922944145
-10-0.00633275874922676
-9-0.06958222069111
-8-0.206589947316864
-7-0.155991023339893
-6-0.148585573540187
-5-0.236245956677284
-4-0.0633035231323822
-30.070451148725369
-20.0884965899717983
-10.277682238060441
00.754341071019633
10.360576561611314
20.152135696015566
30.00395335065846136
4-0.122650771630128
5-0.144817041193761
6-0.116608200432777
7-0.0848275861059149
8-0.209657651486885
9-0.113018552129397
10-0.000358512567110602
11-0.0526583922490606
120.00713356317374315
130.137397518185232
140.126034948567124

\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
-14 & 0.0581787837405573 \tabularnewline
-13 & -0.00900806387794153 \tabularnewline
-12 & 0.0504019422117691 \tabularnewline
-11 & 0.087582922944145 \tabularnewline
-10 & -0.00633275874922676 \tabularnewline
-9 & -0.06958222069111 \tabularnewline
-8 & -0.206589947316864 \tabularnewline
-7 & -0.155991023339893 \tabularnewline
-6 & -0.148585573540187 \tabularnewline
-5 & -0.236245956677284 \tabularnewline
-4 & -0.0633035231323822 \tabularnewline
-3 & 0.070451148725369 \tabularnewline
-2 & 0.0884965899717983 \tabularnewline
-1 & 0.277682238060441 \tabularnewline
0 & 0.754341071019633 \tabularnewline
1 & 0.360576561611314 \tabularnewline
2 & 0.152135696015566 \tabularnewline
3 & 0.00395335065846136 \tabularnewline
4 & -0.122650771630128 \tabularnewline
5 & -0.144817041193761 \tabularnewline
6 & -0.116608200432777 \tabularnewline
7 & -0.0848275861059149 \tabularnewline
8 & -0.209657651486885 \tabularnewline
9 & -0.113018552129397 \tabularnewline
10 & -0.000358512567110602 \tabularnewline
11 & -0.0526583922490606 \tabularnewline
12 & 0.00713356317374315 \tabularnewline
13 & 0.137397518185232 \tabularnewline
14 & 0.126034948567124 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6204&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]-14[/C][C]0.0581787837405573[/C][/ROW]
[ROW][C]-13[/C][C]-0.00900806387794153[/C][/ROW]
[ROW][C]-12[/C][C]0.0504019422117691[/C][/ROW]
[ROW][C]-11[/C][C]0.087582922944145[/C][/ROW]
[ROW][C]-10[/C][C]-0.00633275874922676[/C][/ROW]
[ROW][C]-9[/C][C]-0.06958222069111[/C][/ROW]
[ROW][C]-8[/C][C]-0.206589947316864[/C][/ROW]
[ROW][C]-7[/C][C]-0.155991023339893[/C][/ROW]
[ROW][C]-6[/C][C]-0.148585573540187[/C][/ROW]
[ROW][C]-5[/C][C]-0.236245956677284[/C][/ROW]
[ROW][C]-4[/C][C]-0.0633035231323822[/C][/ROW]
[ROW][C]-3[/C][C]0.070451148725369[/C][/ROW]
[ROW][C]-2[/C][C]0.0884965899717983[/C][/ROW]
[ROW][C]-1[/C][C]0.277682238060441[/C][/ROW]
[ROW][C]0[/C][C]0.754341071019633[/C][/ROW]
[ROW][C]1[/C][C]0.360576561611314[/C][/ROW]
[ROW][C]2[/C][C]0.152135696015566[/C][/ROW]
[ROW][C]3[/C][C]0.00395335065846136[/C][/ROW]
[ROW][C]4[/C][C]-0.122650771630128[/C][/ROW]
[ROW][C]5[/C][C]-0.144817041193761[/C][/ROW]
[ROW][C]6[/C][C]-0.116608200432777[/C][/ROW]
[ROW][C]7[/C][C]-0.0848275861059149[/C][/ROW]
[ROW][C]8[/C][C]-0.209657651486885[/C][/ROW]
[ROW][C]9[/C][C]-0.113018552129397[/C][/ROW]
[ROW][C]10[/C][C]-0.000358512567110602[/C][/ROW]
[ROW][C]11[/C][C]-0.0526583922490606[/C][/ROW]
[ROW][C]12[/C][C]0.00713356317374315[/C][/ROW]
[ROW][C]13[/C][C]0.137397518185232[/C][/ROW]
[ROW][C]14[/C][C]0.126034948567124[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6204&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6204&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])
-140.0581787837405573
-13-0.00900806387794153
-120.0504019422117691
-110.087582922944145
-10-0.00633275874922676
-9-0.06958222069111
-8-0.206589947316864
-7-0.155991023339893
-6-0.148585573540187
-5-0.236245956677284
-4-0.0633035231323822
-30.070451148725369
-20.0884965899717983
-10.277682238060441
00.754341071019633
10.360576561611314
20.152135696015566
30.00395335065846136
4-0.122650771630128
5-0.144817041193761
6-0.116608200432777
7-0.0848275861059149
8-0.209657651486885
9-0.113018552129397
10-0.000358512567110602
11-0.0526583922490606
120.00713356317374315
130.137397518185232
140.126034948567124


Figures (Output of Computation)

Input Parameters & R Code

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