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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 computationThu, 11 Dec 2008 11:16:51 -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/11/t1229019474eje2ij3s0tu04n8.htm/, Retrieved Sun, 19 May 2024 07:22:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=32419, Retrieved Sun, 19 May 2024 07:22:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136

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 II] [2008-12-11 18:16:51] [a9e6d7cd6e144e8b311d9f96a24c5a25] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
2648,9
2669,6
3042,3
2604,2
2732,1
2621,7
2483,7
2479,3
2684,6
2834,7
2566,1
2251,2
2350
2299,8
2542,8
2530,2
2508,1
2616,8
2534,1
2181,8
2578,9
2841,9
2529,9
2103,2
2326,2
2452,6
2782,1
2727,3
2648,2
2760,7
2613
2225,4
2713,9
2923,3
2707
2473,9
2521
2531,8
3068,8
2826,9
2674,2
2966,6
2798,8
2629,6
3124,6
3115,7
3083
2863,9
2728,7
2789,4
3225,7
3148,2
2836,5
3153,5
2656,9
2834,7
3172,5
2998,8
3103,1
2735,6
2818,1
2874,4
3438,5
2949,1
3306,8
3530
3003,8
3206,4
3514,6
3522,6
3525,5
2996,2
3231,1
3030
3541,7
3113,2
3390,8
3424,2
3079,8
3123,4
3317,1
3579,9
3317,9
2668,1
Dataseries Y:
Download CSV
Histogram 
99,5
93,5
104,6
95,3
102,8
103,3
100,2
107,9
107,5
119,8
112
102,1
105,3
101,3
108,4
107,4
109,1
109,5
111,4
110,1
117
129,6
113,5
113,3
110,1
107,4
110,1
112,5
106
117,6
117,8
113,5
121,2
130,4
115,2
117,9
110,7
107,6
124,3
115,1
112,5
127,9
117,4
119,3
130,4
126
125,4
130,5
115,9
108,7
124
119,4
118,6
131,3
111,1
124,8
132,3
126,7
131,7
130,9
122,1
113,2
133,6
119,2
129,4
131,4
117,1
130,5
132,3
140,8
137,5
128,6
126,7
120,8
139,3
128,6
131,3
136,3
128,8
133,2
136,3
151,1
145
134,4

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time0 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 & 0 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32419&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]0 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=32419&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32419&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 time0 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135






Cross Correlation Function
ParameterValue
Box-Cox transformation parameter (lambda) of X series0
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.222292435433401
-14-0.114867100765955
-130.0162501693372221
-12-0.0500576792704274
-11-0.263583872999669
-100.363127123346153
-9-0.129341300039788
-8-0.252258657371735
-70.225746953838978
-60.126987370164697
-5-0.172853008312953
-40.243506418170308
-3-0.178754803963593
-2-0.163545358239958
-10.539372243134289
0-0.457672543993108
10.164260483179948
20.251243342025011
3-0.177504435945417
40.113789899660286
5-0.0094513295118092
6-0.200900481377601
70.0941903829977353
80.179810220576605
9-0.375583631714719
100.168904329531500
110.120695068402038
12-0.174346302196050
130.169893557214132
14-0.132310637138195
15-0.146249705296625

\begin{tabular}{lllllllll}
\hline
Cross Correlation Function \tabularnewline
Parameter & Value \tabularnewline
Box-Cox transformation parameter (lambda) of X series & 0 \tabularnewline
Degree of non-seasonal differencing (d) of X series & 1 \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 \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 & 0.222292435433401 \tabularnewline
-14 & -0.114867100765955 \tabularnewline
-13 & 0.0162501693372221 \tabularnewline
-12 & -0.0500576792704274 \tabularnewline
-11 & -0.263583872999669 \tabularnewline
-10 & 0.363127123346153 \tabularnewline
-9 & -0.129341300039788 \tabularnewline
-8 & -0.252258657371735 \tabularnewline
-7 & 0.225746953838978 \tabularnewline
-6 & 0.126987370164697 \tabularnewline
-5 & -0.172853008312953 \tabularnewline
-4 & 0.243506418170308 \tabularnewline
-3 & -0.178754803963593 \tabularnewline
-2 & -0.163545358239958 \tabularnewline
-1 & 0.539372243134289 \tabularnewline
0 & -0.457672543993108 \tabularnewline
1 & 0.164260483179948 \tabularnewline
2 & 0.251243342025011 \tabularnewline
3 & -0.177504435945417 \tabularnewline
4 & 0.113789899660286 \tabularnewline
5 & -0.0094513295118092 \tabularnewline
6 & -0.200900481377601 \tabularnewline
7 & 0.0941903829977353 \tabularnewline
8 & 0.179810220576605 \tabularnewline
9 & -0.375583631714719 \tabularnewline
10 & 0.168904329531500 \tabularnewline
11 & 0.120695068402038 \tabularnewline
12 & -0.174346302196050 \tabularnewline
13 & 0.169893557214132 \tabularnewline
14 & -0.132310637138195 \tabularnewline
15 & -0.146249705296625 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=32419&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[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of X series[/C][C]1[/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[/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]0.222292435433401[/C][/ROW]
[ROW][C]-14[/C][C]-0.114867100765955[/C][/ROW]
[ROW][C]-13[/C][C]0.0162501693372221[/C][/ROW]
[ROW][C]-12[/C][C]-0.0500576792704274[/C][/ROW]
[ROW][C]-11[/C][C]-0.263583872999669[/C][/ROW]
[ROW][C]-10[/C][C]0.363127123346153[/C][/ROW]
[ROW][C]-9[/C][C]-0.129341300039788[/C][/ROW]
[ROW][C]-8[/C][C]-0.252258657371735[/C][/ROW]
[ROW][C]-7[/C][C]0.225746953838978[/C][/ROW]
[ROW][C]-6[/C][C]0.126987370164697[/C][/ROW]
[ROW][C]-5[/C][C]-0.172853008312953[/C][/ROW]
[ROW][C]-4[/C][C]0.243506418170308[/C][/ROW]
[ROW][C]-3[/C][C]-0.178754803963593[/C][/ROW]
[ROW][C]-2[/C][C]-0.163545358239958[/C][/ROW]
[ROW][C]-1[/C][C]0.539372243134289[/C][/ROW]
[ROW][C]0[/C][C]-0.457672543993108[/C][/ROW]
[ROW][C]1[/C][C]0.164260483179948[/C][/ROW]
[ROW][C]2[/C][C]0.251243342025011[/C][/ROW]
[ROW][C]3[/C][C]-0.177504435945417[/C][/ROW]
[ROW][C]4[/C][C]0.113789899660286[/C][/ROW]
[ROW][C]5[/C][C]-0.0094513295118092[/C][/ROW]
[ROW][C]6[/C][C]-0.200900481377601[/C][/ROW]
[ROW][C]7[/C][C]0.0941903829977353[/C][/ROW]
[ROW][C]8[/C][C]0.179810220576605[/C][/ROW]
[ROW][C]9[/C][C]-0.375583631714719[/C][/ROW]
[ROW][C]10[/C][C]0.168904329531500[/C][/ROW]
[ROW][C]11[/C][C]0.120695068402038[/C][/ROW]
[ROW][C]12[/C][C]-0.174346302196050[/C][/ROW]
[ROW][C]13[/C][C]0.169893557214132[/C][/ROW]
[ROW][C]14[/C][C]-0.132310637138195[/C][/ROW]
[ROW][C]15[/C][C]-0.146249705296625[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=32419&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=32419&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
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.222292435433401
-14-0.114867100765955
-130.0162501693372221
-12-0.0500576792704274
-11-0.263583872999669
-100.363127123346153
-9-0.129341300039788
-8-0.252258657371735
-70.225746953838978
-60.126987370164697
-5-0.172853008312953
-40.243506418170308
-3-0.178754803963593
-2-0.163545358239958
-10.539372243134289
0-0.457672543993108
10.164260483179948
20.251243342025011
3-0.177504435945417
40.113789899660286
5-0.0094513295118092
6-0.200900481377601
70.0941903829977353
80.179810220576605
9-0.375583631714719
100.168904329531500
110.120695068402038
12-0.174346302196050
130.169893557214132
14-0.132310637138195
15-0.146249705296625


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0.0 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 0.0 ; par6 = 0 ; par7 = 1 ;
Parameters (R input):
par1 = 0.0 ; par2 = 1 ; par3 = 1 ; par4 = 12 ; par5 = 0.0 ; 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')