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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 computationSat, 01 Dec 2007 07:23:45 -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/01/t1196518384omof2ty97xaxj02.htm/, Retrieved Sun, 19 May 2024 17:14:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=2261, Retrieved Sun, 19 May 2024 17:14:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact189

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] [assessment worksh...] [2007-12-01 14:23:45] [246ad84e93fbdd1336f5cbee368cde93] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
101.5
99.2
107.8
92.3
99.2
101.6
87.0
71.4
104.7
115.1
102.5
75.3
96.7
94.6
98.6
99.5
92.0
93.6
89.3
66.9
108.8
113.2
105.5
77.8
102.1
97.0
95.5
99.3
86.4
92.4
85.7
61.9
104.9
107.9
95.6
79.8
94.8
93.7
108.1
96.9
88.8
106.7
86.8
69.8
110.9
105.4
99.2
84.4
87.2
91.9
97.9
94.5
85.0
100.3
78.7
65.8
104.8
96.0
103.3
82.9
91.4
94.5
109.3
92.1
99.3
109.6
87.5
73.1
110.7
111.6
110.7
84.0
101.6
102.1
113.9
99.0
100.4
109.5
93.0
76.8
105.3
Dataseries Y:
Download CSV
Histogram 
99.4
102.7
109.3
93.9
95.3
101.8
85.6
81.1
109.5
104.0
94.5
79.0
92.8
95.6
101.7
90.8
89.5
91.8
83.8
77.4
112.7
98.8
85.7
72.8
96.9
95.0
94.2
87.3
80.6
87.9
79.6
71.9
94.6
91.4
86.6
68.5
90.1
91.6
95.4
85.4
81.6
88.9
84.1
74.7
97.1
95.3
85.1
67.3
80.6
87.9
89.2
81.3
79.7
83.7
82.1
69.3
91.2
85.7
85.2
70.0
85.8
91.4
97.5
87.1
85.1
94.1
85.8
74.7
99.9
90.7
86.8
74.8
91.8
97.6
100.8
85.4
84.0
90.6
80.5
73.9
93.6

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=2261&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=2261&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2261&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 series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.0244539306422244
-140.110823716545763
-13-0.141396496977499
-120.127529775234194
-11-0.0362413591911407
-10-0.0231956648289719
-9-0.0307570470576005
-80.082532202411149
-70.00317776045936476
-6-0.0127198861253174
-5-0.0396221852829152
-4-0.106518049817718
-30.0260851842969724
-20.152969112263073
-10.0430512079885259
0-0.268496564570415
10.0674784463350405
20.0417709651548547
3-0.0446702597706123
40.0388599413687282
50.033611561382479
6-0.0245470384491129
7-0.0684583844792021
8-0.00368819222629586
90.047789510874416
100.0837413614488735
11-0.0241125881214046
12-0.188906747644693
130.146484844581675
140.0867401691274323
15-0.094590640414496

\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 & 1 \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 & 1 \tabularnewline
Degree of seasonal differencing (D) of Y series & 1 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-15 & 0.0244539306422244 \tabularnewline
-14 & 0.110823716545763 \tabularnewline
-13 & -0.141396496977499 \tabularnewline
-12 & 0.127529775234194 \tabularnewline
-11 & -0.0362413591911407 \tabularnewline
-10 & -0.0231956648289719 \tabularnewline
-9 & -0.0307570470576005 \tabularnewline
-8 & 0.082532202411149 \tabularnewline
-7 & 0.00317776045936476 \tabularnewline
-6 & -0.0127198861253174 \tabularnewline
-5 & -0.0396221852829152 \tabularnewline
-4 & -0.106518049817718 \tabularnewline
-3 & 0.0260851842969724 \tabularnewline
-2 & 0.152969112263073 \tabularnewline
-1 & 0.0430512079885259 \tabularnewline
0 & -0.268496564570415 \tabularnewline
1 & 0.0674784463350405 \tabularnewline
2 & 0.0417709651548547 \tabularnewline
3 & -0.0446702597706123 \tabularnewline
4 & 0.0388599413687282 \tabularnewline
5 & 0.033611561382479 \tabularnewline
6 & -0.0245470384491129 \tabularnewline
7 & -0.0684583844792021 \tabularnewline
8 & -0.00368819222629586 \tabularnewline
9 & 0.047789510874416 \tabularnewline
10 & 0.0837413614488735 \tabularnewline
11 & -0.0241125881214046 \tabularnewline
12 & -0.188906747644693 \tabularnewline
13 & 0.146484844581675 \tabularnewline
14 & 0.0867401691274323 \tabularnewline
15 & -0.094590640414496 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=2261&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]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[/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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]0.0244539306422244[/C][/ROW]
[ROW][C]-14[/C][C]0.110823716545763[/C][/ROW]
[ROW][C]-13[/C][C]-0.141396496977499[/C][/ROW]
[ROW][C]-12[/C][C]0.127529775234194[/C][/ROW]
[ROW][C]-11[/C][C]-0.0362413591911407[/C][/ROW]
[ROW][C]-10[/C][C]-0.0231956648289719[/C][/ROW]
[ROW][C]-9[/C][C]-0.0307570470576005[/C][/ROW]
[ROW][C]-8[/C][C]0.082532202411149[/C][/ROW]
[ROW][C]-7[/C][C]0.00317776045936476[/C][/ROW]
[ROW][C]-6[/C][C]-0.0127198861253174[/C][/ROW]
[ROW][C]-5[/C][C]-0.0396221852829152[/C][/ROW]
[ROW][C]-4[/C][C]-0.106518049817718[/C][/ROW]
[ROW][C]-3[/C][C]0.0260851842969724[/C][/ROW]
[ROW][C]-2[/C][C]0.152969112263073[/C][/ROW]
[ROW][C]-1[/C][C]0.0430512079885259[/C][/ROW]
[ROW][C]0[/C][C]-0.268496564570415[/C][/ROW]
[ROW][C]1[/C][C]0.0674784463350405[/C][/ROW]
[ROW][C]2[/C][C]0.0417709651548547[/C][/ROW]
[ROW][C]3[/C][C]-0.0446702597706123[/C][/ROW]
[ROW][C]4[/C][C]0.0388599413687282[/C][/ROW]
[ROW][C]5[/C][C]0.033611561382479[/C][/ROW]
[ROW][C]6[/C][C]-0.0245470384491129[/C][/ROW]
[ROW][C]7[/C][C]-0.0684583844792021[/C][/ROW]
[ROW][C]8[/C][C]-0.00368819222629586[/C][/ROW]
[ROW][C]9[/C][C]0.047789510874416[/C][/ROW]
[ROW][C]10[/C][C]0.0837413614488735[/C][/ROW]
[ROW][C]11[/C][C]-0.0241125881214046[/C][/ROW]
[ROW][C]12[/C][C]-0.188906747644693[/C][/ROW]
[ROW][C]13[/C][C]0.146484844581675[/C][/ROW]
[ROW][C]14[/C][C]0.0867401691274323[/C][/ROW]
[ROW][C]15[/C][C]-0.094590640414496[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=2261&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=2261&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 series1
Seasonal Period (s)12
Box-Cox transformation parameter (lambda) of Y series1
Degree of non-seasonal differencing (d) of Y series1
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.0244539306422244
-140.110823716545763
-13-0.141396496977499
-120.127529775234194
-11-0.0362413591911407
-10-0.0231956648289719
-9-0.0307570470576005
-80.082532202411149
-70.00317776045936476
-6-0.0127198861253174
-5-0.0396221852829152
-4-0.106518049817718
-30.0260851842969724
-20.152969112263073
-10.0430512079885259
0-0.268496564570415
10.0674784463350405
20.0417709651548547
3-0.0446702597706123
40.0388599413687282
50.033611561382479
6-0.0245470384491129
7-0.0684583844792021
8-0.00368819222629586
90.047789510874416
100.0837413614488735
11-0.0241125881214046
12-0.188906747644693
130.146484844581675
140.0867401691274323
15-0.094590640414496


Figures (Output of Computation)

Input Parameters & R Code

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