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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 computationWed, 17 Dec 2008 03:28:49 -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/17/t1229509783k0afoqta4t1t3sz.htm/, Retrieved Sun, 19 May 2024 05:12:22 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=34294, Retrieved Sun, 19 May 2024 05:12:22 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact205

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [(Partial) Autocorrelation Function] [(P)ACF Transportm...] [2008-12-04 18:19:15] [65eec331235880e0070acfba94c20cfa]
- RMPD  [Cross Correlation Function] [Cross Correlation...] [2008-12-09 17:38:05] [74be16979710d4c4e7c6647856088456]
-   PD      [Cross Correlation Function] [sqddssssdsss] [2008-12-17 10:28:49] [d41d8cd98f00b204e9800998ecf8427e] [Current]
-   PD        [Cross Correlation Function] [gvgfkjhgl;kjhg] [2008-12-18 09:49:28] [74be16979710d4c4e7c6647856088456]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
105,2
91,5
75,3
60,5
80,4
84,5
93,9
78
92,3
90
72,1
76,9
76
88,7
55,4
46,6
90,9
84,9
89
90,2
72,3
83
71,6
75,4
85,1
81,2
68,7
68,4
93,7
96,6
101,8
93,6
88,9
114,1
82,3
96,4
104
88,2
85,2
87,1
85,5
89,1
105,2
82,9
86,8
112
97,4
88,9
109,4
87,8
90,5
79,3
114,9
118,8
125
96,1
116,7
119,5
104,1
121
127,3
117,7
108
89,4
137,4
142
137,3
122,8
126,1
147,6
115,7
139,2
151,2
123,8
109
112,1
136,4
135,5
138,7
137,5
141,5
143,6
146,5
200,7
196,2
Dataseries Y:
Download CSV
Histogram 
104,7
115,1
102,5
75,3
96,7
94,6
98,6
99,5
92
93,6
89,3
66,9
108,8
113,2
105,5
77,8
102,1
97
95,5
99,3
86,4
92,4
85,7
61,9
104,9
107,9
95,6
79,8
94,8
93,7
108,1
96,9
88,8
106,7
86,8
69,8
110,9
105,4
99,2
84,4
87,2
91,9
97,9
94,5
85
100,3
78,7
65,8
104,8
96
103,3
82,9
91,4
94,5
109,3
92,1
99,3
109,6
87,5
73,1
110,7
111,6
110,7
84
101,6
102,1
113,9
99
100,4
109,5
93,1
77
108
119,9
105,9
78,2
100,3
102,2
97
101,3
89,2
93,3
88,5
61,5
95

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 1 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34294&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34294&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34294&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 time1 seconds
R Server'George Udny Yule' @ 72.249.76.132






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series0.1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
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 series1
krho(Y[t],X[t+k])
-15-0.264864266126915
-14-0.123262704152532
-13-0.292094179207501
-12-0.0737024926570416
-11-0.039051975449394
-10-0.120128466460050
-9-0.0146319808156519
-80.158812950222386
-70.0458839843601195
-60.325006471441665
-50.196371418314434
-40.283735176883743
-30.267557524591212
-20.200928088898367
-10.189159327487970
00.267170154678919
10.0560390072555288
20.168387548234952
30.188223182220145
4-0.0439352968020927
50.0639208869748714
6-0.0159400563380182
7-0.0818702233306514
8-0.0992033744426376
9-0.0398763577455863
10-0.145117602068174
11-0.0534935036095387
12-0.126397707872071
13-0.0864851939747114
14-0.080073445357406
15-0.0328831999999557

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0.1 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 0 \tabularnewline
Degree of seasonal differencing (D) of X series & 1 \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 & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & -0.264864266126915 \tabularnewline
-14 & -0.123262704152532 \tabularnewline
-13 & -0.292094179207501 \tabularnewline
-12 & -0.0737024926570416 \tabularnewline
-11 & -0.039051975449394 \tabularnewline
-10 & -0.120128466460050 \tabularnewline
-9 & -0.0146319808156519 \tabularnewline
-8 & 0.158812950222386 \tabularnewline
-7 & 0.0458839843601195 \tabularnewline
-6 & 0.325006471441665 \tabularnewline
-5 & 0.196371418314434 \tabularnewline
-4 & 0.283735176883743 \tabularnewline
-3 & 0.267557524591212 \tabularnewline
-2 & 0.200928088898367 \tabularnewline
-1 & 0.189159327487970 \tabularnewline
0 & 0.267170154678919 \tabularnewline
1 & 0.0560390072555288 \tabularnewline
2 & 0.168387548234952 \tabularnewline
3 & 0.188223182220145 \tabularnewline
4 & -0.0439352968020927 \tabularnewline
5 & 0.0639208869748714 \tabularnewline
6 & -0.0159400563380182 \tabularnewline
7 & -0.0818702233306514 \tabularnewline
8 & -0.0992033744426376 \tabularnewline
9 & -0.0398763577455863 \tabularnewline
10 & -0.145117602068174 \tabularnewline
11 & -0.0534935036095387 \tabularnewline
12 & -0.126397707872071 \tabularnewline
13 & -0.0864851939747114 \tabularnewline
14 & -0.080073445357406 \tabularnewline
15 & -0.0328831999999557 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=34294&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]0.1[/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]1[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]-0.264864266126915[/C][/ROW]
[ROW][C]-14[/C][C]-0.123262704152532[/C][/ROW]
[ROW][C]-13[/C][C]-0.292094179207501[/C][/ROW]
[ROW][C]-12[/C][C]-0.0737024926570416[/C][/ROW]
[ROW][C]-11[/C][C]-0.039051975449394[/C][/ROW]
[ROW][C]-10[/C][C]-0.120128466460050[/C][/ROW]
[ROW][C]-9[/C][C]-0.0146319808156519[/C][/ROW]
[ROW][C]-8[/C][C]0.158812950222386[/C][/ROW]
[ROW][C]-7[/C][C]0.0458839843601195[/C][/ROW]
[ROW][C]-6[/C][C]0.325006471441665[/C][/ROW]
[ROW][C]-5[/C][C]0.196371418314434[/C][/ROW]
[ROW][C]-4[/C][C]0.283735176883743[/C][/ROW]
[ROW][C]-3[/C][C]0.267557524591212[/C][/ROW]
[ROW][C]-2[/C][C]0.200928088898367[/C][/ROW]
[ROW][C]-1[/C][C]0.189159327487970[/C][/ROW]
[ROW][C]0[/C][C]0.267170154678919[/C][/ROW]
[ROW][C]1[/C][C]0.0560390072555288[/C][/ROW]
[ROW][C]2[/C][C]0.168387548234952[/C][/ROW]
[ROW][C]3[/C][C]0.188223182220145[/C][/ROW]
[ROW][C]4[/C][C]-0.0439352968020927[/C][/ROW]
[ROW][C]5[/C][C]0.0639208869748714[/C][/ROW]
[ROW][C]6[/C][C]-0.0159400563380182[/C][/ROW]
[ROW][C]7[/C][C]-0.0818702233306514[/C][/ROW]
[ROW][C]8[/C][C]-0.0992033744426376[/C][/ROW]
[ROW][C]9[/C][C]-0.0398763577455863[/C][/ROW]
[ROW][C]10[/C][C]-0.145117602068174[/C][/ROW]
[ROW][C]11[/C][C]-0.0534935036095387[/C][/ROW]
[ROW][C]12[/C][C]-0.126397707872071[/C][/ROW]
[ROW][C]13[/C][C]-0.0864851939747114[/C][/ROW]
[ROW][C]14[/C][C]-0.080073445357406[/C][/ROW]
[ROW][C]15[/C][C]-0.0328831999999557[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=34294&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=34294&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 series0.1
Degree of non-seasonal differencing (d) of X series0
Degree of seasonal differencing (D) of X series1
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 series1
krho(Y[t],X[t+k])
-15-0.264864266126915
-14-0.123262704152532
-13-0.292094179207501
-12-0.0737024926570416
-11-0.039051975449394
-10-0.120128466460050
-9-0.0146319808156519
-80.158812950222386
-70.0458839843601195
-60.325006471441665
-50.196371418314434
-40.283735176883743
-30.267557524591212
-20.200928088898367
-10.189159327487970
00.267170154678919
10.0560390072555288
20.168387548234952
30.188223182220145
4-0.0439352968020927
50.0639208869748714
6-0.0159400563380182
7-0.0818702233306514
8-0.0992033744426376
9-0.0398763577455863
10-0.145117602068174
11-0.0534935036095387
12-0.126397707872071
13-0.0864851939747114
14-0.080073445357406
15-0.0328831999999557


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.1 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 1 ;
Parameters (R input):
par1 = 0.1 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 1 ;
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')