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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 computationWed, 16 Dec 2009 06:50:02 -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/2009/Dec/16/t1260971433164r3y98xduzvep.htm/, Retrieved Tue, 30 Apr 2024 20:40:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=68337, Retrieved Tue, 30 Apr 2024 20:40:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact98

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...] [2009-12-16 13:50:02] [1c773da0103d9327c2f1f790e2d74438] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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
Dataseries Y:
Download CSV
Histogram 
101.5
99.2
107.8
92.3
99.2
101.6
87
71.4
104.7
115.1
102.5
75.3
96.7
94.6
98.6
99.5
92
93.6
89.3
66.9
108.8
113.2
105.5
77.8
102.1
97
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
100.3
78.7
65.8
104.8
96
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
101.6
102.1
113.9
99
100.4
109.5
93
76.8
105.3

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=68337&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=68337&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68337&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 series1
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 series1
Degree of non-seasonal differencing (d) of Y series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.0128191249652803
-140.0292492280476033
-13-0.146357039983588
-120.12324080467437
-110.0265523754428649
-100.0212488765126266
-90.0884374356545532
-80.144613208943611
-70.0247062065948913
-60.0842038549901819
-50.210158153423923
-4-0.129809271658286
-30.166123936988443
-2-0.0393816544765438
-10.156606426629491
0-0.193945835630556
1-0.113128579463868
2-0.0368156900576917
3-0.102206432856667
4-0.129701582639304
5-0.192348918885880
6-0.0555479137459363
7-0.250399645350876
80.105196004641696
9-0.176694368769830
10-0.0321364429698777
11-0.0394862598006494
120.0135110931804455
130.0617502615661826
140.00867587443607028
150.0450032408205069

\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 & 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 & 1 \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 & 0.0128191249652803 \tabularnewline
-14 & 0.0292492280476033 \tabularnewline
-13 & -0.146357039983588 \tabularnewline
-12 & 0.12324080467437 \tabularnewline
-11 & 0.0265523754428649 \tabularnewline
-10 & 0.0212488765126266 \tabularnewline
-9 & 0.0884374356545532 \tabularnewline
-8 & 0.144613208943611 \tabularnewline
-7 & 0.0247062065948913 \tabularnewline
-6 & 0.0842038549901819 \tabularnewline
-5 & 0.210158153423923 \tabularnewline
-4 & -0.129809271658286 \tabularnewline
-3 & 0.166123936988443 \tabularnewline
-2 & -0.0393816544765438 \tabularnewline
-1 & 0.156606426629491 \tabularnewline
0 & -0.193945835630556 \tabularnewline
1 & -0.113128579463868 \tabularnewline
2 & -0.0368156900576917 \tabularnewline
3 & -0.102206432856667 \tabularnewline
4 & -0.129701582639304 \tabularnewline
5 & -0.192348918885880 \tabularnewline
6 & -0.0555479137459363 \tabularnewline
7 & -0.250399645350876 \tabularnewline
8 & 0.105196004641696 \tabularnewline
9 & -0.176694368769830 \tabularnewline
10 & -0.0321364429698777 \tabularnewline
11 & -0.0394862598006494 \tabularnewline
12 & 0.0135110931804455 \tabularnewline
13 & 0.0617502615661826 \tabularnewline
14 & 0.00867587443607028 \tabularnewline
15 & 0.0450032408205069 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=68337&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]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]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]1[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-15[/C][C]0.0128191249652803[/C][/ROW]
[ROW][C]-14[/C][C]0.0292492280476033[/C][/ROW]
[ROW][C]-13[/C][C]-0.146357039983588[/C][/ROW]
[ROW][C]-12[/C][C]0.12324080467437[/C][/ROW]
[ROW][C]-11[/C][C]0.0265523754428649[/C][/ROW]
[ROW][C]-10[/C][C]0.0212488765126266[/C][/ROW]
[ROW][C]-9[/C][C]0.0884374356545532[/C][/ROW]
[ROW][C]-8[/C][C]0.144613208943611[/C][/ROW]
[ROW][C]-7[/C][C]0.0247062065948913[/C][/ROW]
[ROW][C]-6[/C][C]0.0842038549901819[/C][/ROW]
[ROW][C]-5[/C][C]0.210158153423923[/C][/ROW]
[ROW][C]-4[/C][C]-0.129809271658286[/C][/ROW]
[ROW][C]-3[/C][C]0.166123936988443[/C][/ROW]
[ROW][C]-2[/C][C]-0.0393816544765438[/C][/ROW]
[ROW][C]-1[/C][C]0.156606426629491[/C][/ROW]
[ROW][C]0[/C][C]-0.193945835630556[/C][/ROW]
[ROW][C]1[/C][C]-0.113128579463868[/C][/ROW]
[ROW][C]2[/C][C]-0.0368156900576917[/C][/ROW]
[ROW][C]3[/C][C]-0.102206432856667[/C][/ROW]
[ROW][C]4[/C][C]-0.129701582639304[/C][/ROW]
[ROW][C]5[/C][C]-0.192348918885880[/C][/ROW]
[ROW][C]6[/C][C]-0.0555479137459363[/C][/ROW]
[ROW][C]7[/C][C]-0.250399645350876[/C][/ROW]
[ROW][C]8[/C][C]0.105196004641696[/C][/ROW]
[ROW][C]9[/C][C]-0.176694368769830[/C][/ROW]
[ROW][C]10[/C][C]-0.0321364429698777[/C][/ROW]
[ROW][C]11[/C][C]-0.0394862598006494[/C][/ROW]
[ROW][C]12[/C][C]0.0135110931804455[/C][/ROW]
[ROW][C]13[/C][C]0.0617502615661826[/C][/ROW]
[ROW][C]14[/C][C]0.00867587443607028[/C][/ROW]
[ROW][C]15[/C][C]0.0450032408205069[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=68337&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=68337&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 series1
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 series0
Degree of seasonal differencing (D) of Y series1
krho(Y[t],X[t+k])
-150.0128191249652803
-140.0292492280476033
-13-0.146357039983588
-120.12324080467437
-110.0265523754428649
-100.0212488765126266
-90.0884374356545532
-80.144613208943611
-70.0247062065948913
-60.0842038549901819
-50.210158153423923
-4-0.129809271658286
-30.166123936988443
-2-0.0393816544765438
-10.156606426629491
0-0.193945835630556
1-0.113128579463868
2-0.0368156900576917
3-0.102206432856667
4-0.129701582639304
5-0.192348918885880
6-0.0555479137459363
7-0.250399645350876
80.105196004641696
9-0.176694368769830
10-0.0321364429698777
11-0.0394862598006494
120.0135110931804455
130.0617502615661826
140.00867587443607028
150.0450032408205069


Figures (Output of Computation)

Input Parameters & R Code

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