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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_cross.wasp
Title produced by softwareCross Correlation Function
Date of computationFri, 19 Dec 2008 05:40:35 -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/19/t1229690520lrwiqn32fuv64s6.htm/, Retrieved Thu, 16 May 2024 00:17:23 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35089, Retrieved Thu, 16 May 2024 00:17:23 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact203

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...] [2008-12-19 12:40:35] [fa8b44cd657c07c6ee11bb2476ca3f8d] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
93.0
99.2
112.2
112.1
103.3
108.2
90.4
72.8
111.0
117.9
111.3
110.5
94.8
100.4
132.1
114.6
101.9
130.2
84.0
86.4
122.3
120.9
110.2
112.6
102.0
105.0
130.5
115.5
103.7
130.9
89.1
93.8
123.8
111.9
118.3
116.9
103.6
116.6
141.3
107.0
125.2
136.4
91.6
95.3
132.3
130.6
131.9
118.6
114.3
111.3
126.5
112.1
119.3
142.4
101.1
97.4
129.1
136.9
129.8
123.9
Dataseries Y:
Download CSV
Histogram 
72.5
72.0
98.8
75.2
81.2
88.0
54.6
68.6
101.5
93.4
84.5
91.4
64.5
64.5
117.3
73.5
79.7
102.6
57.9
73.1
102.4
82.3
89.1
84.7
81.4
67.5
113.9
83.8
73.9
103.9
67.9
62.5
125.4
79.1
106.3
96.2
94.3
85.6
117.4
88.5
124.2
119.3
76.8
70.6
122.1
109.5
119.9
102.3
79.6
78.2
103.6
77.8
99.1
105.7
84.1
88.7
108.0
98.1
101.0
82.0

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'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35089&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35089&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35089&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'Gwilym Jenkins' @ 72.249.127.135






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series2
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-1.6
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0307392263991332
-12-0.282612914648779
-11-0.20884852205063
-100.151454549945859
-90.0562905347197076
-8-0.0593202866885528
-7-0.000730878153626547
-6-0.145122161782402
-50.0392019406613046
-4-0.196152138400212
-30.0447325307944345
-20.108417270722317
-10.0561473117455123
00.400357364936897
10.118195946311526
20.0457135848106886
30.130497833458746
40.0195557329054944
50.0488774565580176
60.121768060875862
7-0.138940857294697
80.175040287248430
9-0.223949182882941
10-0.00658997590815523
110.0716258141026668
12-0.125466797667940
13-0.06395645387293

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 2 \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 & -1.6 \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
-13 & -0.0307392263991332 \tabularnewline
-12 & -0.282612914648779 \tabularnewline
-11 & -0.20884852205063 \tabularnewline
-10 & 0.151454549945859 \tabularnewline
-9 & 0.0562905347197076 \tabularnewline
-8 & -0.0593202866885528 \tabularnewline
-7 & -0.000730878153626547 \tabularnewline
-6 & -0.145122161782402 \tabularnewline
-5 & 0.0392019406613046 \tabularnewline
-4 & -0.196152138400212 \tabularnewline
-3 & 0.0447325307944345 \tabularnewline
-2 & 0.108417270722317 \tabularnewline
-1 & 0.0561473117455123 \tabularnewline
0 & 0.400357364936897 \tabularnewline
1 & 0.118195946311526 \tabularnewline
2 & 0.0457135848106886 \tabularnewline
3 & 0.130497833458746 \tabularnewline
4 & 0.0195557329054944 \tabularnewline
5 & 0.0488774565580176 \tabularnewline
6 & 0.121768060875862 \tabularnewline
7 & -0.138940857294697 \tabularnewline
8 & 0.175040287248430 \tabularnewline
9 & -0.223949182882941 \tabularnewline
10 & -0.00658997590815523 \tabularnewline
11 & 0.0716258141026668 \tabularnewline
12 & -0.125466797667940 \tabularnewline
13 & -0.06395645387293 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35089&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]2[/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]-1.6[/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]-13[/C][C]-0.0307392263991332[/C][/ROW]
[ROW][C]-12[/C][C]-0.282612914648779[/C][/ROW]
[ROW][C]-11[/C][C]-0.20884852205063[/C][/ROW]
[ROW][C]-10[/C][C]0.151454549945859[/C][/ROW]
[ROW][C]-9[/C][C]0.0562905347197076[/C][/ROW]
[ROW][C]-8[/C][C]-0.0593202866885528[/C][/ROW]
[ROW][C]-7[/C][C]-0.000730878153626547[/C][/ROW]
[ROW][C]-6[/C][C]-0.145122161782402[/C][/ROW]
[ROW][C]-5[/C][C]0.0392019406613046[/C][/ROW]
[ROW][C]-4[/C][C]-0.196152138400212[/C][/ROW]
[ROW][C]-3[/C][C]0.0447325307944345[/C][/ROW]
[ROW][C]-2[/C][C]0.108417270722317[/C][/ROW]
[ROW][C]-1[/C][C]0.0561473117455123[/C][/ROW]
[ROW][C]0[/C][C]0.400357364936897[/C][/ROW]
[ROW][C]1[/C][C]0.118195946311526[/C][/ROW]
[ROW][C]2[/C][C]0.0457135848106886[/C][/ROW]
[ROW][C]3[/C][C]0.130497833458746[/C][/ROW]
[ROW][C]4[/C][C]0.0195557329054944[/C][/ROW]
[ROW][C]5[/C][C]0.0488774565580176[/C][/ROW]
[ROW][C]6[/C][C]0.121768060875862[/C][/ROW]
[ROW][C]7[/C][C]-0.138940857294697[/C][/ROW]
[ROW][C]8[/C][C]0.175040287248430[/C][/ROW]
[ROW][C]9[/C][C]-0.223949182882941[/C][/ROW]
[ROW][C]10[/C][C]-0.00658997590815523[/C][/ROW]
[ROW][C]11[/C][C]0.0716258141026668[/C][/ROW]
[ROW][C]12[/C][C]-0.125466797667940[/C][/ROW]
[ROW][C]13[/C][C]-0.06395645387293[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35089&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35089&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 series2
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-1.6
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-13-0.0307392263991332
-12-0.282612914648779
-11-0.20884852205063
-100.151454549945859
-90.0562905347197076
-8-0.0593202866885528
-7-0.000730878153626547
-6-0.145122161782402
-50.0392019406613046
-4-0.196152138400212
-30.0447325307944345
-20.108417270722317
-10.0561473117455123
00.400357364936897
10.118195946311526
20.0457135848106886
30.130497833458746
40.0195557329054944
50.0488774565580176
60.121768060875862
7-0.138940857294697
80.175040287248430
9-0.223949182882941
10-0.00658997590815523
110.0716258141026668
12-0.125466797667940
13-0.06395645387293


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 2.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = -1.6 ; par6 = 0 ; par7 = 1 ;
Parameters (R input):
par1 = 2.0 ; par2 = 0 ; par3 = 1 ; par4 = 12 ; par5 = -1.6 ; 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')