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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 computationTue, 02 Dec 2008 11:17:51 -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/2008/Dec/02/t1228241925wee171k3lv5nk52.htm/, Retrieved Sat, 25 May 2024 10:37:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=28201, Retrieved Sat, 25 May 2024 10:37:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact154

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] [] [2008-12-02 18:17:51] [4bfb60a31ddb9e916b556888a89b5ee8] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101
98,7
105,1
98,4
101,7
102,9
92,2
94,9
92,8
98,5
94,3
87,4
103,4
101,2
109,6
111,9
108,9
105,6
107,8
97,5
102,4
105,6
99,8
96,2
113,1
107,4
116,8
112,9
105,3
109,3
107,9
101,1
114,7
116,2
108,4
113,4
108,7
112,6
124,2
114,9
110,5
121,5
118,1
111,7
132,7
119
116,7
120,1
113,4
106,6
116,3
112,6
111,6
125,1
110,7
109,6
114,2
113,4
116
109,6
117,8
115,8
125,3
113
120,5
116,6
111,8
115,2
118,6
122,4
116,4
114,5
119,8
115,8
127,8
118,8
119,7
118,6
120,8
115,9
109,7
114,8
116,2
112,2
Dataseries Y:
Download CSV
Histogram 
106,7
110,2
125,9
100,1
106,4
114,8
81,3
87
104,2
108
105
94,5
92
95,9
108,8
103,4
102,1
110,1
83,2
82,7
106,8
113,7
102,5
96,6
92,1
95,6
102,3
98,6
98,2
104,5
84
73,8
103,9
106
97,2
102,6
89
93,8
116,7
106,8
98,5
118,7
90
91,9
113,3
113,1
104,1
108,7
96,7
101
116,9
105,8
99
129,4
83
88,9
115,9
104,2
113,4
112,2
100,8
107,3
126,6
102,9
117,9
128,8
87,5
93,8
122,7
126,2
124,6
116,7
115,2
111,1
129,9
113,3
118,5
137,9
103,6
101,7
127,4
137,5
128,3
118,2

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=28201&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=28201&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28201&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])
-160.169156811724545
-150.341180499723429
-140.278334157587126
-130.233936567644690
-120.517354523253882
-110.327835109475686
-100.132393718829334
-90.398011812849801
-80.41218368010864
-70.345283216853814
-60.46601968780359
-50.345268287255439
-40.190779202192336
-30.403519221202142
-20.248881150700652
-10.231610022516878
00.500156685944054
10.224095402485062
20.0839580715512744
30.222047233515664
40.20954485812069
50.158958656889154
60.140065440116304
70.0330832591760699
8-0.0788377744736028
90.0538287814431768
10-0.0351773251017636
11-0.0271324857314652
120.134757427909453
13-0.0104577586134414
14-0.119234213401516
15-0.043198968121464
16-0.0167434244362093

\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
-16 & 0.169156811724545 \tabularnewline
-15 & 0.341180499723429 \tabularnewline
-14 & 0.278334157587126 \tabularnewline
-13 & 0.233936567644690 \tabularnewline
-12 & 0.517354523253882 \tabularnewline
-11 & 0.327835109475686 \tabularnewline
-10 & 0.132393718829334 \tabularnewline
-9 & 0.398011812849801 \tabularnewline
-8 & 0.41218368010864 \tabularnewline
-7 & 0.345283216853814 \tabularnewline
-6 & 0.46601968780359 \tabularnewline
-5 & 0.345268287255439 \tabularnewline
-4 & 0.190779202192336 \tabularnewline
-3 & 0.403519221202142 \tabularnewline
-2 & 0.248881150700652 \tabularnewline
-1 & 0.231610022516878 \tabularnewline
0 & 0.500156685944054 \tabularnewline
1 & 0.224095402485062 \tabularnewline
2 & 0.0839580715512744 \tabularnewline
3 & 0.222047233515664 \tabularnewline
4 & 0.20954485812069 \tabularnewline
5 & 0.158958656889154 \tabularnewline
6 & 0.140065440116304 \tabularnewline
7 & 0.0330832591760699 \tabularnewline
8 & -0.0788377744736028 \tabularnewline
9 & 0.0538287814431768 \tabularnewline
10 & -0.0351773251017636 \tabularnewline
11 & -0.0271324857314652 \tabularnewline
12 & 0.134757427909453 \tabularnewline
13 & -0.0104577586134414 \tabularnewline
14 & -0.119234213401516 \tabularnewline
15 & -0.043198968121464 \tabularnewline
16 & -0.0167434244362093 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=28201&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]-16[/C][C]0.169156811724545[/C][/ROW]
[ROW][C]-15[/C][C]0.341180499723429[/C][/ROW]
[ROW][C]-14[/C][C]0.278334157587126[/C][/ROW]
[ROW][C]-13[/C][C]0.233936567644690[/C][/ROW]
[ROW][C]-12[/C][C]0.517354523253882[/C][/ROW]
[ROW][C]-11[/C][C]0.327835109475686[/C][/ROW]
[ROW][C]-10[/C][C]0.132393718829334[/C][/ROW]
[ROW][C]-9[/C][C]0.398011812849801[/C][/ROW]
[ROW][C]-8[/C][C]0.41218368010864[/C][/ROW]
[ROW][C]-7[/C][C]0.345283216853814[/C][/ROW]
[ROW][C]-6[/C][C]0.46601968780359[/C][/ROW]
[ROW][C]-5[/C][C]0.345268287255439[/C][/ROW]
[ROW][C]-4[/C][C]0.190779202192336[/C][/ROW]
[ROW][C]-3[/C][C]0.403519221202142[/C][/ROW]
[ROW][C]-2[/C][C]0.248881150700652[/C][/ROW]
[ROW][C]-1[/C][C]0.231610022516878[/C][/ROW]
[ROW][C]0[/C][C]0.500156685944054[/C][/ROW]
[ROW][C]1[/C][C]0.224095402485062[/C][/ROW]
[ROW][C]2[/C][C]0.0839580715512744[/C][/ROW]
[ROW][C]3[/C][C]0.222047233515664[/C][/ROW]
[ROW][C]4[/C][C]0.20954485812069[/C][/ROW]
[ROW][C]5[/C][C]0.158958656889154[/C][/ROW]
[ROW][C]6[/C][C]0.140065440116304[/C][/ROW]
[ROW][C]7[/C][C]0.0330832591760699[/C][/ROW]
[ROW][C]8[/C][C]-0.0788377744736028[/C][/ROW]
[ROW][C]9[/C][C]0.0538287814431768[/C][/ROW]
[ROW][C]10[/C][C]-0.0351773251017636[/C][/ROW]
[ROW][C]11[/C][C]-0.0271324857314652[/C][/ROW]
[ROW][C]12[/C][C]0.134757427909453[/C][/ROW]
[ROW][C]13[/C][C]-0.0104577586134414[/C][/ROW]
[ROW][C]14[/C][C]-0.119234213401516[/C][/ROW]
[ROW][C]15[/C][C]-0.043198968121464[/C][/ROW]
[ROW][C]16[/C][C]-0.0167434244362093[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=28201&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=28201&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])
-160.169156811724545
-150.341180499723429
-140.278334157587126
-130.233936567644690
-120.517354523253882
-110.327835109475686
-100.132393718829334
-90.398011812849801
-80.41218368010864
-70.345283216853814
-60.46601968780359
-50.345268287255439
-40.190779202192336
-30.403519221202142
-20.248881150700652
-10.231610022516878
00.500156685944054
10.224095402485062
20.0839580715512744
30.222047233515664
40.20954485812069
50.158958656889154
60.140065440116304
70.0330832591760699
8-0.0788377744736028
90.0538287814431768
10-0.0351773251017636
11-0.0271324857314652
120.134757427909453
13-0.0104577586134414
14-0.119234213401516
15-0.043198968121464
16-0.0167434244362093


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')