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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, 14 Dec 2007 05:30:51 -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/2007/Dec/14/t11976346539dx3co8idffwrba.htm/, Retrieved Thu, 02 May 2024 22:40:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=3855, Retrieved Thu, 02 May 2024 22:40:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact175

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] [oliezaden] [2007-12-14 12:30:51] [a98121933c09d0d44a9f89053acd1df1] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
99.5
101.6
103.9
106.6
108.3
102
93.8
91.6
97.7
94.8
98
103.8
97.8
91.2
89.3
87.5
90.4
94.2
102.2
101.3
96
90.8
93.2
90.9
91.1
90.2
94.3
96
99
103.3
113.1
112.8
112.1
107.4
111
110.5
110.8
112.4
111.5
116.2
122.5
121.3
113.9
110.7
120.8
141.1
147.4
148
158.1
165
187
190.3
182.4
168.8
151.2
120.1
112.5
106.2
107.1
108.5
106.5
108.3
125.6
124
127.2
136.9
135.8
124.3
115.4
113.6
114.4
118.4
117
116.5
115.4
113.6
117.4
116.9
116.4
111.1
110.2
118.9
131.8
130.6
138.3
148.4
148.7
144.3
152.5
162.9
167.2
166.5
185.6
Dataseries Y:
Download CSV
Histogram 
112.1
104.2
102.4
100.3
102.6
101.5
103.4
99.4
97.9
98
90.2
87.1
91.8
94.8
91.8
89.3
91.7
86.2
82.8
82.3
79.8
79.4
85.3
87.5
88.3
88.6
94.9
94.7
92.6
91.8
96.4
96.4
107.1
111.9
107.8
109.2
115.3
119.2
107.8
106.8
104.2
94.8
97.5
98.3
100.6
94.9
93.6
98
104.3
103.9
105.3
102.6
103.3
107.9
107.8
109.8
110.6
110.8
119.3
128.1
127.6
137.9
151.4
143.6
143.4
141.9
135.2
133.1
129.6
134.1
136.8
143.5
162.5
163.1
157.2
158.8
155.4
148.5
154.2
153.3
149.4
147.9
156
163
159.1
159.5
157.3
156.4
156.6
162.4
166.8
162.6
168.1

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=3855&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=3855&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3855&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 series1
Degree of seasonal differencing (D) of X series0
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 series0
krho(Y[t],X[t+k])
-16-0.149765963004922
-15-0.194898132304542
-140.0933414372430635
-130.154051151202779
-120.112434828099887
-110.155108714616905
-100.148248473724157
-90.0581010321973339
-80.156898954162114
-7-0.0443238862193213
-6-0.177753929781978
-5-0.113373738811483
-4-0.175561557963328
-3-0.0857015297674159
-2-0.0275250629023257
-1-0.0798491217413775
00.0707804704464603
1-0.0284442036327535
20.0741208753226428
30.183798091174715
40.099414924768736
5-0.150449817851848
6-0.0726892888592865
7-0.155498787188160
8-0.152354497407700
9-0.00635457566584437
100.042352814037727
11-0.0560949007386703
120.057355879333548
130.179743483935732
140.253324672545100
150.0385393625576976
160.018688317492747

\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 & 0 \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 & 0 \tabularnewline
k & rho(Y[t],X[t+k]) \tabularnewline
-16 & -0.149765963004922 \tabularnewline
-15 & -0.194898132304542 \tabularnewline
-14 & 0.0933414372430635 \tabularnewline
-13 & 0.154051151202779 \tabularnewline
-12 & 0.112434828099887 \tabularnewline
-11 & 0.155108714616905 \tabularnewline
-10 & 0.148248473724157 \tabularnewline
-9 & 0.0581010321973339 \tabularnewline
-8 & 0.156898954162114 \tabularnewline
-7 & -0.0443238862193213 \tabularnewline
-6 & -0.177753929781978 \tabularnewline
-5 & -0.113373738811483 \tabularnewline
-4 & -0.175561557963328 \tabularnewline
-3 & -0.0857015297674159 \tabularnewline
-2 & -0.0275250629023257 \tabularnewline
-1 & -0.0798491217413775 \tabularnewline
0 & 0.0707804704464603 \tabularnewline
1 & -0.0284442036327535 \tabularnewline
2 & 0.0741208753226428 \tabularnewline
3 & 0.183798091174715 \tabularnewline
4 & 0.099414924768736 \tabularnewline
5 & -0.150449817851848 \tabularnewline
6 & -0.0726892888592865 \tabularnewline
7 & -0.155498787188160 \tabularnewline
8 & -0.152354497407700 \tabularnewline
9 & -0.00635457566584437 \tabularnewline
10 & 0.042352814037727 \tabularnewline
11 & -0.0560949007386703 \tabularnewline
12 & 0.057355879333548 \tabularnewline
13 & 0.179743483935732 \tabularnewline
14 & 0.253324672545100 \tabularnewline
15 & 0.0385393625576976 \tabularnewline
16 & 0.018688317492747 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=3855&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]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]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]0[/C][/ROW]
[ROW][C]k[/C][C]rho(Y[t],X[t+k])[/C][/ROW]
[ROW][C]-16[/C][C]-0.149765963004922[/C][/ROW]
[ROW][C]-15[/C][C]-0.194898132304542[/C][/ROW]
[ROW][C]-14[/C][C]0.0933414372430635[/C][/ROW]
[ROW][C]-13[/C][C]0.154051151202779[/C][/ROW]
[ROW][C]-12[/C][C]0.112434828099887[/C][/ROW]
[ROW][C]-11[/C][C]0.155108714616905[/C][/ROW]
[ROW][C]-10[/C][C]0.148248473724157[/C][/ROW]
[ROW][C]-9[/C][C]0.0581010321973339[/C][/ROW]
[ROW][C]-8[/C][C]0.156898954162114[/C][/ROW]
[ROW][C]-7[/C][C]-0.0443238862193213[/C][/ROW]
[ROW][C]-6[/C][C]-0.177753929781978[/C][/ROW]
[ROW][C]-5[/C][C]-0.113373738811483[/C][/ROW]
[ROW][C]-4[/C][C]-0.175561557963328[/C][/ROW]
[ROW][C]-3[/C][C]-0.0857015297674159[/C][/ROW]
[ROW][C]-2[/C][C]-0.0275250629023257[/C][/ROW]
[ROW][C]-1[/C][C]-0.0798491217413775[/C][/ROW]
[ROW][C]0[/C][C]0.0707804704464603[/C][/ROW]
[ROW][C]1[/C][C]-0.0284442036327535[/C][/ROW]
[ROW][C]2[/C][C]0.0741208753226428[/C][/ROW]
[ROW][C]3[/C][C]0.183798091174715[/C][/ROW]
[ROW][C]4[/C][C]0.099414924768736[/C][/ROW]
[ROW][C]5[/C][C]-0.150449817851848[/C][/ROW]
[ROW][C]6[/C][C]-0.0726892888592865[/C][/ROW]
[ROW][C]7[/C][C]-0.155498787188160[/C][/ROW]
[ROW][C]8[/C][C]-0.152354497407700[/C][/ROW]
[ROW][C]9[/C][C]-0.00635457566584437[/C][/ROW]
[ROW][C]10[/C][C]0.042352814037727[/C][/ROW]
[ROW][C]11[/C][C]-0.0560949007386703[/C][/ROW]
[ROW][C]12[/C][C]0.057355879333548[/C][/ROW]
[ROW][C]13[/C][C]0.179743483935732[/C][/ROW]
[ROW][C]14[/C][C]0.253324672545100[/C][/ROW]
[ROW][C]15[/C][C]0.0385393625576976[/C][/ROW]
[ROW][C]16[/C][C]0.018688317492747[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=3855&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=3855&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 series0
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 series0
krho(Y[t],X[t+k])
-16-0.149765963004922
-15-0.194898132304542
-140.0933414372430635
-130.154051151202779
-120.112434828099887
-110.155108714616905
-100.148248473724157
-90.0581010321973339
-80.156898954162114
-7-0.0443238862193213
-6-0.177753929781978
-5-0.113373738811483
-4-0.175561557963328
-3-0.0857015297674159
-2-0.0275250629023257
-1-0.0798491217413775
00.0707804704464603
1-0.0284442036327535
20.0741208753226428
30.183798091174715
40.099414924768736
5-0.150449817851848
6-0.0726892888592865
7-0.155498787188160
8-0.152354497407700
9-0.00635457566584437
100.042352814037727
11-0.0560949007386703
120.057355879333548
130.179743483935732
140.253324672545100
150.0385393625576976
160.018688317492747


Figures (Output of Computation)

Input Parameters & R Code

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