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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 computationThu, 04 Dec 2008 10:48:32 -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/04/t1228415384tcnxlrx6bbq16k4.htm/, Retrieved Wed, 22 May 2024 07:34:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=29002, Retrieved Wed, 22 May 2024 07:34:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact177

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] [2008-12-04 17:48:32] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
100,8
105,3
116,1
112,8
114,5
117,2
77,1
80,1
120,3
133,4
109,4
93,2
91,2
99,2
108,2
101,5
106,9
104,4
77,9
60
99,5
95
105,6
102,5
93,3
97,3
127
111,7
96,4
133
72,2
95,8
124,1
127,6
110,7
104,6
112,7
115,3
139,4
119
97,4
154
81,5
88,8
127,7
105,1
114,9
106,4
104,5
121,6
141,4
99
126,7
134,1
81,3
88,6
132,7
132,9
134,4
103,7
119,7
115
132,9
108,5
113,9
142
97,7
92,2
128,8
134,9
128,2
114,8
117,9
Dataseries Y:
Download CSV
Histogram 
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
117.1

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=29002&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=29002&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29002&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 series-0.1
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 series-0.4
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-14-0.185642577202209
-13-0.178533877815991
-12-0.349997192342948
-11-0.201741750266231
-10-0.183525938282440
-9-0.127826490890470
-80.0850837091505585
-7-0.136725439356688
-6-0.00100774402554271
-50.161876521851067
-40.0843273103367418
-30.257860894439718
-20.261736986451246
-10.0962055499986587
00.792624771443763
10.241418850162448
20.374327477203851
30.315994371464004
40.10639680797942
50.296680130644615
60.338989655500296
7-0.0501330568144861
80.133179675036901
9-0.0265968860454624
10-0.146700549831676
110.0265511230772577
12-0.367995308918522
13-0.179338834524554
14-0.273265283061481

\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 & -0.4 \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
-14 & -0.185642577202209 \tabularnewline
-13 & -0.178533877815991 \tabularnewline
-12 & -0.349997192342948 \tabularnewline
-11 & -0.201741750266231 \tabularnewline
-10 & -0.183525938282440 \tabularnewline
-9 & -0.127826490890470 \tabularnewline
-8 & 0.0850837091505585 \tabularnewline
-7 & -0.136725439356688 \tabularnewline
-6 & -0.00100774402554271 \tabularnewline
-5 & 0.161876521851067 \tabularnewline
-4 & 0.0843273103367418 \tabularnewline
-3 & 0.257860894439718 \tabularnewline
-2 & 0.261736986451246 \tabularnewline
-1 & 0.0962055499986587 \tabularnewline
0 & 0.792624771443763 \tabularnewline
1 & 0.241418850162448 \tabularnewline
2 & 0.374327477203851 \tabularnewline
3 & 0.315994371464004 \tabularnewline
4 & 0.10639680797942 \tabularnewline
5 & 0.296680130644615 \tabularnewline
6 & 0.338989655500296 \tabularnewline
7 & -0.0501330568144861 \tabularnewline
8 & 0.133179675036901 \tabularnewline
9 & -0.0265968860454624 \tabularnewline
10 & -0.146700549831676 \tabularnewline
11 & 0.0265511230772577 \tabularnewline
12 & -0.367995308918522 \tabularnewline
13 & -0.179338834524554 \tabularnewline
14 & -0.273265283061481 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=29002&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]-0.4[/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]-14[/C][C]-0.185642577202209[/C][/ROW]
[ROW][C]-13[/C][C]-0.178533877815991[/C][/ROW]
[ROW][C]-12[/C][C]-0.349997192342948[/C][/ROW]
[ROW][C]-11[/C][C]-0.201741750266231[/C][/ROW]
[ROW][C]-10[/C][C]-0.183525938282440[/C][/ROW]
[ROW][C]-9[/C][C]-0.127826490890470[/C][/ROW]
[ROW][C]-8[/C][C]0.0850837091505585[/C][/ROW]
[ROW][C]-7[/C][C]-0.136725439356688[/C][/ROW]
[ROW][C]-6[/C][C]-0.00100774402554271[/C][/ROW]
[ROW][C]-5[/C][C]0.161876521851067[/C][/ROW]
[ROW][C]-4[/C][C]0.0843273103367418[/C][/ROW]
[ROW][C]-3[/C][C]0.257860894439718[/C][/ROW]
[ROW][C]-2[/C][C]0.261736986451246[/C][/ROW]
[ROW][C]-1[/C][C]0.0962055499986587[/C][/ROW]
[ROW][C]0[/C][C]0.792624771443763[/C][/ROW]
[ROW][C]1[/C][C]0.241418850162448[/C][/ROW]
[ROW][C]2[/C][C]0.374327477203851[/C][/ROW]
[ROW][C]3[/C][C]0.315994371464004[/C][/ROW]
[ROW][C]4[/C][C]0.10639680797942[/C][/ROW]
[ROW][C]5[/C][C]0.296680130644615[/C][/ROW]
[ROW][C]6[/C][C]0.338989655500296[/C][/ROW]
[ROW][C]7[/C][C]-0.0501330568144861[/C][/ROW]
[ROW][C]8[/C][C]0.133179675036901[/C][/ROW]
[ROW][C]9[/C][C]-0.0265968860454624[/C][/ROW]
[ROW][C]10[/C][C]-0.146700549831676[/C][/ROW]
[ROW][C]11[/C][C]0.0265511230772577[/C][/ROW]
[ROW][C]12[/C][C]-0.367995308918522[/C][/ROW]
[ROW][C]13[/C][C]-0.179338834524554[/C][/ROW]
[ROW][C]14[/C][C]-0.273265283061481[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=29002&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=29002&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 series-0.1
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 series-0.4
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-14-0.185642577202209
-13-0.178533877815991
-12-0.349997192342948
-11-0.201741750266231
-10-0.183525938282440
-9-0.127826490890470
-80.0850837091505585
-7-0.136725439356688
-6-0.00100774402554271
-50.161876521851067
-40.0843273103367418
-30.257860894439718
-20.261736986451246
-10.0962055499986587
00.792624771443763
10.241418850162448
20.374327477203851
30.315994371464004
40.10639680797942
50.296680130644615
60.338989655500296
7-0.0501330568144861
80.133179675036901
9-0.0265968860454624
10-0.146700549831676
110.0265511230772577
12-0.367995308918522
13-0.179338834524554
14-0.273265283061481


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 0 ; par3 = 0 ; par4 = 1 ;
Parameters (R input):
par1 = -0.1 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = -0.4 ; 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')