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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 computationFri, 07 Dec 2007 06:50:50 -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/Dec/07/t1197034709h4355ou4k8nvn6d.htm/, Retrieved Sun, 28 Apr 2024 23:28:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2826, Retrieved Sun, 28 Apr 2024 23:28:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

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...] [2007-12-07 13:50:50] [9bb499d88394279c02e6a8b8cf177cf7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
18.33
22.6
24.9
24.8
23.8
25.1
26
27.4
27.3
24.3
28.4
24.4
30.3
31.5
29.8
25.3
25.6
26.7
27.4
28.6
26.3
28.5
28.4
29.4
30.3
29.6
32.1
32.4
36.3
34.6
36.3
40.3
40.4
45.4
39
35.7
40.2
41.7
49.1
49.6
47
52
53.1
57.8
57.9
54.6
51.3
52.7
58.5
56.6
57.9
64.4
65.1
64.6
68.9
68.8
59.3
55
55.4
58
50.8
54.6
58.6
63.6
64.5
66.9
71.9
68.7
74.2
75.8
Dataseries Y:
Download CSV
Histogram 
9041.46
9476.91
9420.10
9690.65
10084.25
10344.12
10086.71
9959.87
10256.23
10172.04
10258.34
10703.35
11484.51
11568.05
10991.80
10545.34
11462.71
11462.40
11285.57
11552.26
12171.38
12174.88
12531.67
13099.33
13331.94
13021.59
13040.64
13030.09
12362.41
12602.89
12794.66
12874.90
13015.84
13495.45
14123.82
14246.00
13652.94
13616.55
13934.98
13773.79
13585.12
13810.92
13657.18
14075.57
14663.08
15107.66
15358.34
16375.51
17602.60
17824.63
17892.97
19639.74
21790.73
19187.52
20357.82
20291.34
19264.86
18858.49
20156.19
20222.50
20251.14
21373.38
21091.86
21856.72
21532.48
21085.27
21388.73
21363.38
22842.24
24231.43

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=2826&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=2826&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2826&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 series0
Degree of non-seasonal differencing (d) of X series1
Degree of seasonal differencing (D) of X series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-150.00302888008303406
-14-0.0189434210378759
-13-0.057456129017971
-12-0.196443073279597
-110.127196594094981
-100.218312358668411
-9-0.0653153586900688
-8-0.0394544001797528
-70.0978939125780883
-60.0695260213069108
-5-0.190434133229378
-40.116421160043113
-30.0225624065138074
-2-0.137239195939518
-1-0.0869819992906972
00.216377181514842
10.0181151682323933
2-0.0634941397846212
30.0516970458008445
40.0327644434252086
5-0.057107786760696
6-0.111906122264892
70.178505580211151
8-0.120461576167718
9-0.0430570112342322
10-0.0495283305901539
11-0.00656299934163994
12-0.130028798837532
13-0.136514801701091
140.111828016948635
15-0.0455578788029073

\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 & 0 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & 0.00302888008303406 \tabularnewline
-14 & -0.0189434210378759 \tabularnewline
-13 & -0.057456129017971 \tabularnewline
-12 & -0.196443073279597 \tabularnewline
-11 & 0.127196594094981 \tabularnewline
-10 & 0.218312358668411 \tabularnewline
-9 & -0.0653153586900688 \tabularnewline
-8 & -0.0394544001797528 \tabularnewline
-7 & 0.0978939125780883 \tabularnewline
-6 & 0.0695260213069108 \tabularnewline
-5 & -0.190434133229378 \tabularnewline
-4 & 0.116421160043113 \tabularnewline
-3 & 0.0225624065138074 \tabularnewline
-2 & -0.137239195939518 \tabularnewline
-1 & -0.0869819992906972 \tabularnewline
0 & 0.216377181514842 \tabularnewline
1 & 0.0181151682323933 \tabularnewline
2 & -0.0634941397846212 \tabularnewline
3 & 0.0516970458008445 \tabularnewline
4 & 0.0327644434252086 \tabularnewline
5 & -0.057107786760696 \tabularnewline
6 & -0.111906122264892 \tabularnewline
7 & 0.178505580211151 \tabularnewline
8 & -0.120461576167718 \tabularnewline
9 & -0.0430570112342322 \tabularnewline
10 & -0.0495283305901539 \tabularnewline
11 & -0.00656299934163994 \tabularnewline
12 & -0.130028798837532 \tabularnewline
13 & -0.136514801701091 \tabularnewline
14 & 0.111828016948635 \tabularnewline
15 & -0.0455578788029073 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2826&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]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]0[/C][/ROW]
[ROW][C]Degree of non-seasonal differencing (d) of Y series[/C][C]1[/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]-15[/C][C]0.00302888008303406[/C][/ROW]
[ROW][C]-14[/C][C]-0.0189434210378759[/C][/ROW]
[ROW][C]-13[/C][C]-0.057456129017971[/C][/ROW]
[ROW][C]-12[/C][C]-0.196443073279597[/C][/ROW]
[ROW][C]-11[/C][C]0.127196594094981[/C][/ROW]
[ROW][C]-10[/C][C]0.218312358668411[/C][/ROW]
[ROW][C]-9[/C][C]-0.0653153586900688[/C][/ROW]
[ROW][C]-8[/C][C]-0.0394544001797528[/C][/ROW]
[ROW][C]-7[/C][C]0.0978939125780883[/C][/ROW]
[ROW][C]-6[/C][C]0.0695260213069108[/C][/ROW]
[ROW][C]-5[/C][C]-0.190434133229378[/C][/ROW]
[ROW][C]-4[/C][C]0.116421160043113[/C][/ROW]
[ROW][C]-3[/C][C]0.0225624065138074[/C][/ROW]
[ROW][C]-2[/C][C]-0.137239195939518[/C][/ROW]
[ROW][C]-1[/C][C]-0.0869819992906972[/C][/ROW]
[ROW][C]0[/C][C]0.216377181514842[/C][/ROW]
[ROW][C]1[/C][C]0.0181151682323933[/C][/ROW]
[ROW][C]2[/C][C]-0.0634941397846212[/C][/ROW]
[ROW][C]3[/C][C]0.0516970458008445[/C][/ROW]
[ROW][C]4[/C][C]0.0327644434252086[/C][/ROW]
[ROW][C]5[/C][C]-0.057107786760696[/C][/ROW]
[ROW][C]6[/C][C]-0.111906122264892[/C][/ROW]
[ROW][C]7[/C][C]0.178505580211151[/C][/ROW]
[ROW][C]8[/C][C]-0.120461576167718[/C][/ROW]
[ROW][C]9[/C][C]-0.0430570112342322[/C][/ROW]
[ROW][C]10[/C][C]-0.0495283305901539[/C][/ROW]
[ROW][C]11[/C][C]-0.00656299934163994[/C][/ROW]
[ROW][C]12[/C][C]-0.130028798837532[/C][/ROW]
[ROW][C]13[/C][C]-0.136514801701091[/C][/ROW]
[ROW][C]14[/C][C]0.111828016948635[/C][/ROW]
[ROW][C]15[/C][C]-0.0455578788029073[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2826&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2826&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 series0
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series0
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series0
krho(Y[t],X[t+k])
-150.00302888008303406
-14-0.0189434210378759
-13-0.057456129017971
-12-0.196443073279597
-110.127196594094981
-100.218312358668411
-9-0.0653153586900688
-8-0.0394544001797528
-70.0978939125780883
-60.0695260213069108
-5-0.190434133229378
-40.116421160043113
-30.0225624065138074
-2-0.137239195939518
-1-0.0869819992906972
00.216377181514842
10.0181151682323933
2-0.0634941397846212
30.0516970458008445
40.0327644434252086
5-0.057107786760696
6-0.111906122264892
70.178505580211151
8-0.120461576167718
9-0.0430570112342322
10-0.0495283305901539
11-0.00656299934163994
12-0.130028798837532
13-0.136514801701091
140.111828016948635
15-0.0455578788029073


Figures (Output of Computation)

Input Parameters & R Code

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