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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, 22 Nov 2007 06:59:25 -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/22/t1195739963gaw04428txjkfkb.htm/, Retrieved Thu, 02 May 2024 18:29:15 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=6005, Retrieved Thu, 02 May 2024 18:29:15 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact191

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] [WS7 Q5 G6 cross cor] [2007-11-22 13:59:25] [fef19078983b9fa83d10cb717d6f9786] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
112,6
113,8
107,8
103,2
103,3
101,2
107,7
110,4
101,9
115,9
89,9
88,6
117,2
123,9
100
103,6
94,1
98,7
119,5
112,7
104,4
124,7
89,1
97
121,6
118,8
114
111,5
97,2
102,5
113,4
109,8
104,9
126,1
80
96,8
117,2
112,3
117,3
111,1
102,2
104,3
122,9
107,6
121,3
131,5
89
104,4
128,9
135,9
133,3
121,3
120,5
120,4
137,9
126,1
133,2
146,6
103,4
117,2
Dataseries Y:
Download CSV
Histogram 
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
142,9
95,2
93

Tables (Output of Computation)





Summary of compuational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6005&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6005&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6005&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 time1 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






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])
-14-0.249061984251497
-13-0.105992768282861
-120.453120018748048
-11-0.079205749443965
-10-0.259625586910973
-90.0705420708723268
-8-0.0487458117112884
-70.0212909748526315
-60.292992526717962
-50.159761161913755
-4-0.0137159107038306
-30.147434470073403
-2-0.142292207515598
-10.111190209904605
00.774301115752176
10.062303576715461
2-0.0703341853385881
30.186567366399782
4-0.0196955252998912
50.138790590298444
60.330814480742092
70.197520132220088
80.0633390134179253
90.103161989414721
10-0.250815583899232
110.0602290617736143
120.562740257404885
13-0.0066850457144075
14-0.0503264914657291

\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 & -0.249061984251497 \tabularnewline
-13 & -0.105992768282861 \tabularnewline
-12 & 0.453120018748048 \tabularnewline
-11 & -0.079205749443965 \tabularnewline
-10 & -0.259625586910973 \tabularnewline
-9 & 0.0705420708723268 \tabularnewline
-8 & -0.0487458117112884 \tabularnewline
-7 & 0.0212909748526315 \tabularnewline
-6 & 0.292992526717962 \tabularnewline
-5 & 0.159761161913755 \tabularnewline
-4 & -0.0137159107038306 \tabularnewline
-3 & 0.147434470073403 \tabularnewline
-2 & -0.142292207515598 \tabularnewline
-1 & 0.111190209904605 \tabularnewline
0 & 0.774301115752176 \tabularnewline
1 & 0.062303576715461 \tabularnewline
2 & -0.0703341853385881 \tabularnewline
3 & 0.186567366399782 \tabularnewline
4 & -0.0196955252998912 \tabularnewline
5 & 0.138790590298444 \tabularnewline
6 & 0.330814480742092 \tabularnewline
7 & 0.197520132220088 \tabularnewline
8 & 0.0633390134179253 \tabularnewline
9 & 0.103161989414721 \tabularnewline
10 & -0.250815583899232 \tabularnewline
11 & 0.0602290617736143 \tabularnewline
12 & 0.562740257404885 \tabularnewline
13 & -0.0066850457144075 \tabularnewline
14 & -0.0503264914657291 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=6005&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]-0.249061984251497[/C][/ROW]
[ROW][C]-13[/C][C]-0.105992768282861[/C][/ROW]
[ROW][C]-12[/C][C]0.453120018748048[/C][/ROW]
[ROW][C]-11[/C][C]-0.079205749443965[/C][/ROW]
[ROW][C]-10[/C][C]-0.259625586910973[/C][/ROW]
[ROW][C]-9[/C][C]0.0705420708723268[/C][/ROW]
[ROW][C]-8[/C][C]-0.0487458117112884[/C][/ROW]
[ROW][C]-7[/C][C]0.0212909748526315[/C][/ROW]
[ROW][C]-6[/C][C]0.292992526717962[/C][/ROW]
[ROW][C]-5[/C][C]0.159761161913755[/C][/ROW]
[ROW][C]-4[/C][C]-0.0137159107038306[/C][/ROW]
[ROW][C]-3[/C][C]0.147434470073403[/C][/ROW]
[ROW][C]-2[/C][C]-0.142292207515598[/C][/ROW]
[ROW][C]-1[/C][C]0.111190209904605[/C][/ROW]
[ROW][C]0[/C][C]0.774301115752176[/C][/ROW]
[ROW][C]1[/C][C]0.062303576715461[/C][/ROW]
[ROW][C]2[/C][C]-0.0703341853385881[/C][/ROW]
[ROW][C]3[/C][C]0.186567366399782[/C][/ROW]
[ROW][C]4[/C][C]-0.0196955252998912[/C][/ROW]
[ROW][C]5[/C][C]0.138790590298444[/C][/ROW]
[ROW][C]6[/C][C]0.330814480742092[/C][/ROW]
[ROW][C]7[/C][C]0.197520132220088[/C][/ROW]
[ROW][C]8[/C][C]0.0633390134179253[/C][/ROW]
[ROW][C]9[/C][C]0.103161989414721[/C][/ROW]
[ROW][C]10[/C][C]-0.250815583899232[/C][/ROW]
[ROW][C]11[/C][C]0.0602290617736143[/C][/ROW]
[ROW][C]12[/C][C]0.562740257404885[/C][/ROW]
[ROW][C]13[/C][C]-0.0066850457144075[/C][/ROW]
[ROW][C]14[/C][C]-0.0503264914657291[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=6005&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=6005&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])
-14-0.249061984251497
-13-0.105992768282861
-120.453120018748048
-11-0.079205749443965
-10-0.259625586910973
-90.0705420708723268
-8-0.0487458117112884
-70.0212909748526315
-60.292992526717962
-50.159761161913755
-4-0.0137159107038306
-30.147434470073403
-2-0.142292207515598
-10.111190209904605
00.774301115752176
10.062303576715461
2-0.0703341853385881
30.186567366399782
4-0.0196955252998912
50.138790590298444
60.330814480742092
70.197520132220088
80.0633390134179253
90.103161989414721
10-0.250815583899232
110.0602290617736143
120.562740257404885
13-0.0066850457144075
14-0.0503264914657291


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 1.0 ; par2 = 0 ; par3 = 0 ; par4 = 12 ; par5 = 1 ; par6 = 0 ; par7 = 0 ;
Parameters (R input):
par1 = 1.0 ; 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) 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')